Huawei Cloud Cloudrobo Dataset

Name: Huawei Cloud Cloudrobo Dataset
Rating: 4.2 (5 reviews)
Author: huaweicloud

Manage CloudRobo data processing (proc-tasks) and data evaluation (eval-tasks) — query algorithms, create/list/show/update/delete/restart tasks; poll task status until terminal; retrieve system and job logs; download logs; preview output data and frames; discover available algorithms from the asset marketplace; orchestrate processing→evaluation pipelines; batch-manage tasks across workspaces; diagnose failures via log analysis. Triggers include: data processing task management, data evaluation task management, task status polling, log retrieval for troubleshooting, output data preview, algorithm discovery, task pipeline orchestration, batch task management, failure diagnosis, dataset, proc-tasks, eval-tasks.

huaweicloud Updated Sep 9, 2026

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File contents

Windows / PowerShell: Examples use bash syntax. To run on Windows PowerShell:

Flatten \ line continuations to a single line, or end lines with a backtick.

Set env vars with $env:NAME="value" instead of export NAME="value".

Single-quoted JSON '{"a":"b"}' works as-is.

Overview

The cloudrobo-dataset skill manages the full lifecycle of CloudRobo data processing (proc-tasks) and data evaluation (eval-tasks). It covers algorithm query, task CRUD operations, status polling, log retrieval (system + job) and download, output data preview, frame extraction, algorithm discovery from the asset marketplace, processing→evaluation pipeline orchestration, batch task management, and failure diagnosis.

Applicable scenarios: Task management (CRUD + restart), troubleshooting (log retrieval + error analysis), algorithm discovery, result verification (preview + frames), pipeline orchestration, batch management, analytics.

Architecture:

Agent / LLM
    │
    ├── CLI  →  cloudrobo dataset proc <command>     (proc-tasks)
    │           cloudrobo dataset eval <command>     (eval-tasks)
    ├── SDK  →  DatasetClient (Python)
                    │
                    ▼
              cloudrobo-service (REST API)
              /v1/data-eng/proc-tasks/*
              /v1/data-eng/eval-tasks/*

All operations target the cloudrobo-service backend and require a workspace_id (default workspace is used unless --workspace-id overrides it). Algorithm and dataset discovery is a cross-package operation that calls the cloudrobo-asset-manager service via cloudrobo asset.

Prerequisites

See references/cli-installation-guide.md for CLI installation, AK/SK authentication, and workspace configuration. All dataset operations require a valid workspace_id (default or explicit --workspace-id).

Workflow

Interactive Task Creation

All interactive creation workflows follow the Interaction Rules: at most one tool call per turn, display query results before asking the next question.

Proc-Task Creation (10 steps): Task name → Description → Algorithm type (PRESET_ASSETS/WORKSPACE_ASSETS/OBS_ASSETS) → Algorithm configuration with field mapping → Environment variables → Job type and resources (CCE/K8S or CCE_RAY/RAY, resource pool, instance spec) → Dynamic storage (public pool only) → Input datasets (multi-dataset loop) → Output configuration → Confirm and submit. See references/interactive-workflow.md for detailed steps.

Eval-Task Creation (7 steps): Task name → Description → Resource pool and instance spec → Evaluation algorithm → Dataset (single) → Robot config → Confirm and submit. See references/interactive-workflow.md for detailed steps.

Task Polling and Result Handling

Poll status — dataset proc wait-task (recommended 15s interval), report each state change to user, until terminal state (SUCCEEDED/FAILED/DELETED)
On completion:
- SUCCEEDED: view processing result via get-preview, output system log
- FAILED: ask user whether to view logs, output system and job logs

Eval tasks: After SUCCEEDED, extract report path from target_report_path in task detail, use dataset eval get-preview --task-id <task-id> --file-name <obs-path-without-bucket> to get OBS temporary link.

Pipeline Workflow (Task Orchestration)

Scenario: data conversion → data evaluation → download artifact

Run processing task, wait for SUCCEEDED
Extract target_path and target_asset_id from task detail
Construct dataset_configs entry with obs_path = target_path, asset_id = target_asset_id
Create evaluation task, wait for SUCCEEDED
Get report: dataset eval get-preview --file-name <path-from-target_report_path> (remove obs://<bucket>/ prefix)
Download artifacts via download-asset

Batch Workflow (Batch Tasks)

Scenario: run same algorithm across multiple datasets

Get dataset list (asset list-assets --type dataset)
Create processing task per dataset (reuse algorithm/resource config from first; only input dataset differs)
Collect task_ids, poll status
Summarize success/failure/in-progress counts
For failed tasks: view logs or restart
Batch delete: proc delete-task --task-id id1,id2,id3

Diagnosis Workflow (Failure Diagnosis)

Scenario: task FAILED → analyze logs, suggest fixes

Get system and user logs
Analyze error patterns: OOM → increase worker_spec.memory; path not found → check dataset_configs; image pull failure → check image; parameter error → check algo_entrance/envs; access denied → check catalog_id/permissions
Output diagnosis and fix suggestions
After confirmation, modify via update-task or restart via restart-task

Analytics Workflow (Data Analysis)

Aggregate task stats by status, algorithm ranking, time trend, failure rate. Output analysis report with root-cause suggestions.

Long-Running Task Workflow

Start wait-task with timeout. On timeout, report status and elapsed time; user decides: continue / view logs / terminate.

CLI Command Format Standard

cloudrobo dataset proc <command> [OPTIONS]
cloudrobo dataset eval <command> [OPTIONS]

Feature	Description	Example
Command group	`dataset proc` (proc-tasks), `dataset eval` (eval-tasks)	`cloudrobo dataset proc`
Subcommand	kebab-case	`create-task`, `list-tasks`, `show-task`
Workspace override	`--workspace-id <id>`	`--workspace-id abc-123`
Output format	JSON to stdout	`out(result)`
Dry-run	`--dry-run` (where supported)	Preview without executing
Boolean flag	`--is-system true`	`--is-system true`
Comma list	`--task-ids id1,id2,id3`	`--task-ids aaa,bbb`

Core Commands

Task Management (proc-tasks)

Create a data processing task

cloudrobo dataset proc create-task --name <task-name> --algo-type PRESET_ASSETS --task-config '<json-config>' [--workspace-id <id>] [--wait] [--timeout 1800] [--dry-run]

SDK: client.create_task(task_config: dict)
API: POST /v1/data-eng/proc-tasks

Required task_config fields: name, algo_type (PRESET_ASSETS / WORKSPACE_ASSETS / OBS_ASSETS, based on Step 3 selection), algo_name, algo_entrance, image, algo_id, catalog_id (workspace's), resource_pool_type, cluster_type, task_framework_type, dataset_configs (JSON string array, multi-dataset input), output_type, output_path, output_name, head_spec (must include cpu/memory/gpu/npu), worker_spec (must include cpu/memory/gpu/npu), worker_num, evs_spec. See references/task-config-catalog.md for full field mapping.

⚠️ Non-Empty Validation: Except description, all parameters cannot be empty values (empty string "", None, empty dict {}). The SDK validates this before API submission. head_spec/worker_spec must include all four keys: cpu, memory, gpu, npu (value 0 is valid). dataset_configs must contain at least 1 dataset entry; empty array "[]" is invalid.

List tasks

cloudrobo dataset proc list-tasks [--status RUNNING|SUCCEEDED|FAILED] [--algo-type <type>] [--name <name>] [--order-by start_at|update_at|finish_at] [--order DESC|ASC] [--offset <n>] [--limit <n>] [--user-id <id>] [--algo-name <name>] [--output-name <name>] [--workspace-id <id>]

SDK: client.list_tasks(workspace_id=None, statuses=..., algo_type=..., name=..., order_by=..., ...)
API: GET /v1/data-eng/proc-tasks?workspace_id=<id>&statuses=<status>

Show task detail

cloudrobo dataset proc show-task --task-id <task-id>

SDK: client.get_task_detail(task_id)
API: GET /v1/data-eng/proc-tasks/{task_id}

Update a task (SDK only)

SDK: client.update_task(task_id, task_config: dict)
API: PATCH /v1/data-eng/proc-tasks/{task_id}

Delete tasks (SDK only)

SDK: client.delete_tasks([task_id_1, task_id_2])
API: DELETE /v1/data-eng/proc-tasks?ids=id1,id2

Restart a task

cloudrobo dataset proc restart-task --task-id <task-id>

SDK: client.restart_task(task_id)
API: POST /v1/data-eng/proc-tasks/{task_id}/restart

Task Monitoring

Wait for task to reach terminal state

cloudrobo dataset proc wait-task --task-id <task-id> [--timeout 1800] [--interval 10]

Terminal states: SUCCEEDED, FAILED, DELETED

SDK: client.wait_task(task_id, timeout=1800, interval=10,>


API: GET /v1/data-eng/proc-tasks/{task_id} (polled)


Retrieve task logs
# Step 1: List log files to get file_path
cloudrobo dataset proc get-log --task-id <id> --is-system true
cloudrobo dataset proc get-log --task-id <id> --is-system false

# Step 2: Get log content (default: latest 64KB tail)
cloudrobo dataset proc get-log --task-id <id> --file-name <name> --file-path <path>

# Get full log (not just tail)
cloudrobo dataset proc get-log --task-id <id> --file-name <name> --file-path <path> --all


SDK: client.list_log_files(task_id, is_system=True) → client.get_task_log(task_id, file_name, file_path, start_byte, end_byte) or client.get_task_log_tail(task_id, file_name)
API:
GET /v1/data-eng/proc-tasks/{task_id}/logs?is_system=true|false
GET /v1/data-eng/proc-tasks/{task_id}/logs/{file_name}?start_byte=&end_byte=&file_path=&job_id=



Download a log file
cloudrobo dataset proc download-log --task-id <id> --file-name <name> --file-path <path>


SDK: client.download_task_log(task_id, file_name, file_path)
API: GET /v1/data-eng/proc-tasks/{task_id}/logs/{file_name}/download

Get task resource usage
cloudrobo dataset proc get-resource-usage --task-id <task-id> --metric CPU_UTIL|CPU_USED_CORE|MEM_UTIL|MEM_USED_MB|NETWORK_TX_RATE|NETWORK_RX_RATE|DISK_READ_KB|DISK_WRITE_KB --start <unix-ts-sec> --end <unix-ts-sec> --step <10-3600>


SDK: client.get_task_resource_usage(task_id, metric, start, end, step)
API: GET /v1/data-eng/proc-tasks/{task_id}/resource-usage?metric=&start=&end=&step=

Data Preview
Preview task output data
Get OBS temporary download link for a dataset file. file_name = OBS path excluding bucket name (e.g., cloudrobo/f91cee72-.../1ddf1498-.../data/chunk-000/file-000.parquet).
cloudrobo dataset proc get-preview --task-id <task-id> --file-name <obs-path-without-bucket>


SDK: client.get_task_preview(task_id, file_name)
API: GET /v1/data-eng/proc-tasks/{task_id}/preview?file_name=<file_name>

Get task frames
Query directory file list of task input/output datasets. prefix = dataset OBS path excluding bucket name (e.g., cloudrobo/f91cee72-.../1ddf1498-.../).
cloudrobo dataset proc get-frames --task-id <task-id> --prefix <obs-path-without-bucket>


SDK: client.get_task_frames(task_id, prefix)
API: GET /v1/data-eng/proc-tasks/{task_id}/frames?prefix=<prefix>

Evaluation Tasks (eval-tasks)
Evaluation tasks differ from processing tasks in field names, deletion granularity, and supported
operations. See the full comparison table in references/task-config-catalog.md.
Create an evaluation task
cloudrobo dataset eval create-task --name <task-name> --task-config '<json-config>' [--workspace-id <id>] [--wait] [--timeout 1800]


SDK: client.create_eval_task(task_config: dict)
API: POST /v1/data-eng/eval-tasks

task-config field description:
The eval-task task-config requires two sets of dataset fields: top-level single-value fields (dataset_type, dataset_id, dataset_name, dataset_path) + dataset_configs array (single dataset, format same as proc-task).
Required fields: name, algo_type, algo_id, algo_name, algo_entrance, image, catalog_id (workspace's), cluster_type, task_framework_type, dataset_type/dataset_id/dataset_name/dataset_path (top-level), dataset_configs, robot_config, resource_pool_type, head_spec, worker_spec, worker_num, evs_spec, output_type, output_path, output_name.
Optional: description, resource_id, dedicated_pool_name.
⚠️ Key reminders:

Both top-level dataset fields and dataset_configs array required
dataset_name cannot be empty (extract from OBS path last directory for UDF_OBS_ASSET)
dataset_type values: BUILD_IN_ASSET / UDF_OBS_ASSET

See references/task-config-catalog.md for full field mapping and eval-task field differences.
List evaluation tasks
cloudrobo dataset eval list-tasks [--status <status>] [--name <name>] [--workspace-id <id>]


SDK: client.list_eval_tasks(workspace_id=None, **params)
API: GET /v1/data-eng/eval-tasks?workspace_id=<id>

Show evaluation task detail
cloudrobo dataset eval show-task --task-id <task-id>


SDK: client.get_eval_task_detail(task_id)
API: GET /v1/data-eng/eval-tasks/{task_id}

Update an evaluation task (SDK only)

SDK: client.update_eval_task(task_id, task_config: dict)
API: PATCH /v1/data-eng/eval-tasks/{task_id}

Delete an evaluation task (single granularity, SDK only)

SDK: client.delete_eval_task(task_id)
API: DELETE /v1/data-eng/eval-tasks/{task_id}

Note: eval-tasks deletion is single-task granularity (delete-task), same as proc-tasks
(delete-task). eval-tasks do not support restart.
Retrieve evaluation task logs
# Step 1: List log files
cloudrobo dataset eval get-log --task-id <id> --is-system true
cloudrobo dataset eval get-log --task-id <id> --is-system false

# Step 2: Get log content
cloudrobo dataset eval get-log --task-id <id> --file-name <name> --file-path <path>


SDK: client.list_eval_log_files(task_id, is_system=True) + client.get_eval_task_log(task_id, file_name, ...)
API:
GET /v1/data-eng/eval-tasks/{task_id}/logs?is_system=true|false
GET /v1/data-eng/eval-tasks/{task_id}/logs/{file_name}?file_path=&job_id=



Get evaluation task preview
file_name is the OBS path of the report file (excluding bucket name). Extract from task detail's target_report_path by removing obs://<bucket-name>/ prefix.
For example: if target_report_path is obs://cloudrobo-test-203/eval_task/report/abc-123/diversity_evaluation_report.pdf, then file_name = eval_task/report/abc-123/diversity_evaluation_report.pdf.
cloudrobo dataset eval get-preview --task-id <task-id> --file-name <obs-path-without-bucket> [--is-download]


SDK: client.get_eval_task_preview(task_id, file_name, is_download=False)
API: GET /v1/data-eng/eval-tasks/{task_id}/preview?file_name=<obs-path-without-bucket>&isDownload=

Returns OBS temporary URL. Use --is-download for download link, omit for preview link. Save or download promptly.
Algorithm Discovery
List available algorithms
cloudrobo asset list-publication-assets --type algorithm --tags "Data Processing" [--name <fuzzy-name>] [--limit 20]


SDK (cross-package): asset_client.list_publication_assets(type="algorithm", sub_type="data_processing", limit=20)
API: Cross-package — calls the asset service, not the dataset service directly.

Each algorithm includes ext_metadata with engine.image_url, command, and
environment_variables needed for task creation. Use --tags "Data Evaluation" to discover
evaluation algorithms.
Reference Documents

CLI Installation Guide — cloudrobo CLI installation and configuration
IAM Policies — Least-privilege credential model
Verification Method — Verification method details
Dataflow Diagram — Mermaid data flow diagram
Acceptance Criteria — Acceptance criteria
Task Config Reference — Algorithm field mapping, required fields template, envs format, eval-tasks field differences
Interactive Workflow — Detailed step-by-step interactive creation workflows for proc-tasks and eval-tasks

Edge Cases



Scenario
Handling



Missing workspace_id
Run cloudrobo workspace use or use --workspace-id


Task in non-terminal state
wait-task polls until SUCCEEDED/FAILED/DELETED or timeout


Log file not found
Falls back to system-std-output.log / job-std-output.log


Large log file
Default 64KB tail; use --all or download-log


Task creation fails
Check algo_type, JSON validity, dataset_configs, resource quota


AK/SK not set
Set HUAWEI_CLOUD_AK/HUAWEI_CLOUD_SK


Algorithm not found
Use --name fuzzy search or sub_type filter


eval-task delete
Single delete only; no batch, no restart


Pipeline input
Wrap target_path into dataset_configs entry


Evaluation report link
OBS temp URL; save/download promptly


envs format
JSON array string, not object; see task-config-catalog.md


catalog_id mismatch
Use workspace's, not algorithm's


list-assets params
Provide --catalog-id or --repository-id; get from cloudrobo workspace current


Algorithm source
Built-in: list-publication-assets; custom: list-assets


dataset_configs
Use asset's url field; don't manually concatenate


Log query
Get file list first for file_path, then fetch content


Task states
Terminal: SUCCEEDED, FAILED, DELETED; non-terminal: CREATING, RUNNING, PENDING, FROZEN


Task deletion
Irreversible


Algorithm fields
Extract from ext_metadata; don't fabricate


Object storage
Must use obs://; s3:// prohibited


API paths
From SDK _url() calls, not inferred


Cross-skill
No training/inference; use cloudrobo-train/infer


Mutating ops
create/update/delete/restart require confirmation


Workflow triggers
No params → interactive; complete params → skip to confirm


Missing optional fields
Skip if no environment_variables; use defaults for worker_spec; prompt for robot_config in eval


Empty field validation
Except description, all params must be non-empty; SDK rejects empty strings/None/empty dicts before submission


head_spec/worker_spec
Must include cpu, memory, gpu, npu keys (value 0 is valid)


dataset_configs empty
Must contain at least 1 dataset entry; empty array "[]" is invalid


Advanced resources
DEDICATED_POOL: query for IDs; Ray: pair cluster/framework types, non-zero head_spec


Verification Method
Specification Compliance Verification
bash scripts/test-cli-commands.sh -s . -e cli

Functional Testing
# CLI / SDK
bash scripts/test-cli-commands.sh -s . -e {cli|sdk}

API-level verification is manual — replay the API paths in
references/task-config-catalog.md in
API Explorer.
Test Cases
See templates/test-vars.json for the full test case list covering proc-tasks, eval-tasks,
algorithm discovery, and pipeline scenarios.
Verification Checklist

After creating a task, poll status (recommended 15s interval), report each state change to user
On SUCCEEDED: verify output via get-preview, output system log
On FAILED: ask user whether to view logs, fetch system and job logs per the two-step flow
(list files → get content)
For pipeline: verify processing target_path is wrapped into dataset_configs for the eval task, then eval
SUCCEEDED → get-preview returns OBS link
For eval tasks: verify report preview after SUCCEEDED

Best Practices

Always run list-algorithms first to discover available operators before creating a task
Use --dry-run with create-task to validate task config before actual execution
Use wait-task with --timeout to avoid indefinite polling; report each status transition
On task failure, retrieve both system logs (--is-system true) and job logs (--is-system false),
analyze error patterns (OOM / path not found / image pull failure / OBS access) and suggest fixes
before restarting
For pipeline orchestration, wait for processing SUCCEEDED before creating evaluation task
Before batch delete, confirm task IDs to avoid irreversible deletion
Clean up completed/failed tasks with delete-task to free resources
Set CLOUDROBO_DEBUG=1 for verbose error output during troubleshooting
Evaluation report links are OBS temporary URLs — save or download promptly

Scenario	Handling
Missing `workspace_id`	Run `cloudrobo workspace use` or use `--workspace-id`
Task in non-terminal state	`wait-task` polls until SUCCEEDED/FAILED/DELETED or timeout
Log file not found	Falls back to `system-std-output.log` / `job-std-output.log`
Large log file	Default 64KB tail; use `--all` or `download-log`
Task creation fails	Check algo_type, JSON validity, dataset_configs, resource quota
AK/SK not set	Set `HUAWEI_CLOUD_AK`/`HUAWEI_CLOUD_SK`
Algorithm not found	Use `--name` fuzzy search or `sub_type` filter
eval-task delete	Single delete only; no batch, no restart
Pipeline input	Wrap `target_path` into `dataset_configs` entry
Evaluation report link	OBS temp URL; save/download promptly
`envs` format	JSON array string, not object; see task-config-catalog.md
`catalog_id` mismatch	Use workspace's, not algorithm's
`list-assets` params	Provide `--catalog-id` or `--repository-id`; get from `cloudrobo workspace current`
Algorithm source	Built-in: `list-publication-assets`; custom: `list-assets`
`dataset_configs`	Use asset's `url` field; don't manually concatenate
Log query	Get file list first for `file_path`, then fetch content
Task states	Terminal: SUCCEEDED, FAILED, DELETED; non-terminal: CREATING, RUNNING, PENDING, FROZEN
Task deletion	Irreversible
Algorithm fields	Extract from `ext_metadata`; don't fabricate
Object storage	Must use `obs://`; `s3://` prohibited
API paths	From SDK `_url()` calls, not inferred
Cross-skill	No training/inference; use cloudrobo-train/infer
Mutating ops	create/update/delete/restart require confirmation
Workflow triggers	No params → interactive; complete params → skip to confirm
Missing optional fields	Skip if no `environment_variables`; use defaults for `worker_spec`; prompt for `robot_config` in eval
Empty field validation	Except `description`, all params must be non-empty; SDK rejects empty strings/None/empty dicts before submission
`head_spec`/`worker_spec`	Must include `cpu`, `memory`, `gpu`, `npu` keys (value `0` is valid)
`dataset_configs` empty	Must contain at least 1 dataset entry; empty array `"[]"` is invalid
Advanced resources	DEDICATED_POOL: query for IDs; Ray: pair cluster/framework types, non-zero head_spec

   1---2name: huawei-cloud-cloudrobo-dataset3description: Manage CloudRobo data processing (proc-tasks) and data evaluation (eval-tasks) — query algorithms, create/list/show/update/delete/restart tasks; poll task status until terminal; retrieve system and job logs; download logs; preview output data and frames; discover available algorithms from the asset marketplace; orchestrate processing→evaluation pipelines; batch-manage tasks across workspaces; diagnose failures via log analysis. Triggers include: data processing task management, data evaluation task management, task status polling, log retrieval for troubleshooting, output data preview, algorithm discovery, task pipeline orchestration, batch task management, failure diagnosis, dataset, proc-tasks, eval-tasks.4---5
6> **Windows / PowerShell:** Examples use bash syntax. To run on Windows PowerShell:
7> - Flatten `\` line continuations to a single line, or end lines with a backtick.
8> - Set env vars with `$env:NAME="value"` instead of `export NAME="value"`.
9> - Single-quoted JSON `'{"a":"b"}'` works as-is.
10
11## Overview
12
13The `cloudrobo-dataset` skill manages the full lifecycle of CloudRobo data processing
14(proc-tasks) and data evaluation (eval-tasks). It covers algorithm query, task CRUD operations,
15status polling, log retrieval (system + job) and download, output data preview, frame extraction,
16algorithm discovery from the asset marketplace, processing→evaluation pipeline orchestration,
17batch task management, and failure diagnosis.
18
19**Applicable scenarios:** Task management (CRUD + restart), troubleshooting (log retrieval + error analysis), algorithm discovery, result verification (preview + frames), pipeline orchestration, batch management, analytics.
20
21**Architecture:**
22
23```
24Agent / LLM
25    │
26    ├── CLI  →  cloudrobo dataset proc <command>     (proc-tasks)
27    │           cloudrobo dataset eval <command>     (eval-tasks)
28    ├── SDK  →  DatasetClient (Python)
29                    │
30                    ▼
31              cloudrobo-service (REST API)
32              /v1/data-eng/proc-tasks/*
33              /v1/data-eng/eval-tasks/*
34```
35
36All operations target the `cloudrobo-service` backend and require a `workspace_id` (default
37workspace is used unless `--workspace-id` overrides it). Algorithm and dataset discovery is a
38cross-package operation that calls the `cloudrobo-asset-manager` service via `cloudrobo asset`.
39
40## Prerequisites
41
42See `references/cli-installation-guide.md` for CLI installation, AK/SK authentication, and
43workspace configuration. All dataset operations require a valid `workspace_id` (default or
44explicit `--workspace-id`).
45
46## Workflow
47
48### Interactive Task Creation
49
50All interactive creation workflows follow the **Interaction Rules**: at most one tool call per turn, display query results before asking the next question.
51
52**Proc-Task Creation** (10 steps): Task name → Description → Algorithm type (PRESET_ASSETS/WORKSPACE_ASSETS/OBS_ASSETS) → Algorithm configuration with field mapping → Environment variables → Job type and resources (CCE/K8S or CCE_RAY/RAY, resource pool, instance spec) → Dynamic storage (public pool only) → Input datasets (multi-dataset loop) → Output configuration → Confirm and submit. See `references/interactive-workflow.md` for detailed steps.
53
54**Eval-Task Creation** (7 steps): Task name → Description → Resource pool and instance spec → Evaluation algorithm → Dataset (single) → Robot config → Confirm and submit. See `references/interactive-workflow.md` for detailed steps.
55
56### Task Polling and Result Handling
57
581. **Poll status** — `dataset proc wait-task` (recommended 15s interval), report each state change to
59   user, until terminal state (SUCCEEDED/FAILED/DELETED)
602. **On completion:**
61   - SUCCEEDED: view processing result via `get-preview`, output system log
62   - FAILED: ask user whether to view logs, output system and job logs
63
64**Eval tasks:** After SUCCEEDED, extract report path from `target_report_path` in task detail, use `dataset eval get-preview --task-id <task-id> --file-name <obs-path-without-bucket>` to get OBS temporary link.
65
66### Pipeline Workflow (Task Orchestration)
67
68Scenario: data conversion → data evaluation → download artifact
69
701. Run processing task, wait for SUCCEEDED
712. Extract `target_path` and `target_asset_id` from task detail
723. Construct `dataset_configs` entry with `obs_path` = `target_path`, `asset_id` = `target_asset_id`
734. Create evaluation task, wait for SUCCEEDED
745. Get report: `dataset eval get-preview --file-name <path-from-target_report_path>` (remove `obs://<bucket>/` prefix)
756. Download artifacts via `download-asset`
76
77### Batch Workflow (Batch Tasks)
78
79Scenario: run same algorithm across multiple datasets
80
811. Get dataset list (`asset list-assets --type dataset`)
822. Create processing task per dataset (reuse algorithm/resource config from first; only input dataset differs)
833. Collect task_ids, poll status
844. Summarize success/failure/in-progress counts
855. For failed tasks: view logs or restart
866. Batch delete: `proc delete-task --task-id id1,id2,id3`
87
88### Diagnosis Workflow (Failure Diagnosis)
89
90Scenario: task FAILED → analyze logs, suggest fixes
91
921. Get system and user logs
932. Analyze error patterns: OOM → increase `worker_spec.memory`; path not found → check `dataset_configs`; image pull failure → check `image`; parameter error → check `algo_entrance`/`envs`; access denied → check `catalog_id`/permissions
943. Output diagnosis and fix suggestions
954. After confirmation, modify via `update-task` or restart via `restart-task`
96
97### Analytics Workflow (Data Analysis)
98
99Aggregate task stats by status, algorithm ranking, time trend, failure rate. Output analysis report with root-cause suggestions.
100
101### Long-Running Task Workflow
102
103Start `wait-task` with timeout. On timeout, report status and elapsed time; user decides: continue / view logs / terminate.
104
105## CLI Command Format Standard
106
107```bash
108cloudrobo dataset proc <command> [OPTIONS]
109cloudrobo dataset eval <command> [OPTIONS]
110```
111
112| Feature | Description | Example |
113|---------|-------------|---------|
114| Command group | `dataset proc` (proc-tasks), `dataset eval` (eval-tasks) | `cloudrobo dataset proc` |
115| Subcommand | kebab-case | `create-task`, `list-tasks`, `show-task` |
116| Workspace override | `--workspace-id <id>` | `--workspace-id abc-123` |
117| Output format | JSON to stdout | `out(result)` |
118| Dry-run | `--dry-run` (where supported) | Preview without executing |
119| Boolean flag | `--is-system true` | `--is-system true` |
120| Comma list | `--task-ids id1,id2,id3` | `--task-ids aaa,bbb` |
121
122## Core Commands
123
124### Task Management (proc-tasks)
125
126#### Create a data processing task
127
128```bash
129cloudrobo dataset proc create-task --name <task-name> --algo-type PRESET_ASSETS --task-config '<json-config>' [--workspace-id <id>] [--wait] [--timeout 1800] [--dry-run]
130```
131
132- **SDK:** `client.create_task(task_config: dict)`
133- **API:** `POST /v1/data-eng/proc-tasks`
134
135Required task_config fields: `name`, `algo_type` (PRESET_ASSETS / WORKSPACE_ASSETS / OBS_ASSETS, based on Step 3 selection), `algo_name`, `algo_entrance`,
136`image`, `algo_id`, `catalog_id` (workspace's), `resource_pool_type`, `cluster_type`,
137`task_framework_type`, `dataset_configs` (JSON string array, multi-dataset input),
138`output_type`, `output_path`, `output_name`, `head_spec` (must include `cpu`/`memory`/`gpu`/`npu`), `worker_spec` (must include `cpu`/`memory`/`gpu`/`npu`), `worker_num`,
139`evs_spec`. See `references/task-config-catalog.md` for full field mapping.
140
141**⚠️ Non-Empty Validation:** Except `description`, all parameters cannot be empty values (empty string `""`, `None`, empty dict `{}`). The SDK validates this before API submission. `head_spec`/`worker_spec` must include all four keys: `cpu`, `memory`, `gpu`, `npu` (value `0` is valid). `dataset_configs` must contain at least 1 dataset entry; empty array `"[]"` is invalid.
142
143#### List tasks
144
145```bash
146cloudrobo dataset proc list-tasks [--status RUNNING|SUCCEEDED|FAILED] [--algo-type <type>] [--name <name>] [--order-by start_at|update_at|finish_at] [--order DESC|ASC] [--offset <n>] [--limit <n>] [--user-id <id>] [--algo-name <name>] [--output-name <name>] [--workspace-id <id>]
147```
148
149- **SDK:** `client.list_tasks(workspace_id=None, statuses=..., algo_type=..., name=..., order_by=..., ...)`
150- **API:** `GET /v1/data-eng/proc-tasks?workspace_id=<id>&statuses=<status>`
151
152#### Show task detail
153
154```bash
155cloudrobo dataset proc show-task --task-id <task-id>
156```
157
158- **SDK:** `client.get_task_detail(task_id)`
159- **API:** `GET /v1/data-eng/proc-tasks/{task_id}`
160
161#### Update a task (SDK only)
162
163- **SDK:** `client.update_task(task_id, task_config: dict)`
164- **API:** `PATCH /v1/data-eng/proc-tasks/{task_id}`
165
166#### Delete tasks (SDK only)
167
168- **SDK:** `client.delete_tasks([task_id_1, task_id_2])`
169- **API:** `DELETE /v1/data-eng/proc-tasks?ids=id1,id2`
170
171#### Restart a task
172
173```bash
174cloudrobo dataset proc restart-task --task-id <task-id>
175```
176
177- **SDK:** `client.restart_task(task_id)`
178- **API:** `POST /v1/data-eng/proc-tasks/{task_id}/restart`
179
180### Task Monitoring
181
182#### Wait for task to reach terminal state
183
184```bash
185cloudrobo dataset proc wait-task --task-id <task-id> [--timeout 1800] [--interval 10]
186```
187
188Terminal states: `SUCCEEDED`, `FAILED`, `DELETED`
189
190- **SDK:** `client.wait_task(task_id, timeout=1800, interval=10, on_status=callback)`
191- **API:** `GET /v1/data-eng/proc-tasks/{task_id}` (polled)
192
193#### Retrieve task logs
194
195```bash
196# Step 1: List log files to get file_path
197cloudrobo dataset proc get-log --task-id <id> --is-system true
198cloudrobo dataset proc get-log --task-id <id> --is-system false
199
200# Step 2: Get log content (default: latest 64KB tail)
201cloudrobo dataset proc get-log --task-id <id> --file-name <name> --file-path <path>
202
203# Get full log (not just tail)
204cloudrobo dataset proc get-log --task-id <id> --file-name <name> --file-path <path> --all
205```
206
207- **SDK:** `client.list_log_files(task_id, is_system=True)` → `client.get_task_log(task_id, file_name, file_path, start_byte, end_byte)` or `client.get_task_log_tail(task_id, file_name)`
208- **API:**
209  - `GET /v1/data-eng/proc-tasks/{task_id}/logs?is_system=true|false`
210  - `GET /v1/data-eng/proc-tasks/{task_id}/logs/{file_name}?start_byte=&end_byte=&file_path=&job_id=`
211
212#### Download a log file
213
214```bash
215cloudrobo dataset proc download-log --task-id <id> --file-name <name> --file-path <path>
216```
217
218- **SDK:** `client.download_task_log(task_id, file_name, file_path)`
219- **API:** `GET /v1/data-eng/proc-tasks/{task_id}/logs/{file_name}/download`
220
221#### Get task resource usage
222
223```bash
224cloudrobo dataset proc get-resource-usage --task-id <task-id> --metric CPU_UTIL|CPU_USED_CORE|MEM_UTIL|MEM_USED_MB|NETWORK_TX_RATE|NETWORK_RX_RATE|DISK_READ_KB|DISK_WRITE_KB --start <unix-ts-sec> --end <unix-ts-sec> --step <10-3600>
225```
226
227- **SDK:** `client.get_task_resource_usage(task_id, metric, start, end, step)`
228- **API:** `GET /v1/data-eng/proc-tasks/{task_id}/resource-usage?metric=&start=&end=&step=`
229
230### Data Preview
231
232#### Preview task output data
233
234Get OBS temporary download link for a dataset file. `file_name` = OBS path excluding bucket name (e.g., `cloudrobo/f91cee72-.../1ddf1498-.../data/chunk-000/file-000.parquet`).
235
236```bash
237cloudrobo dataset proc get-preview --task-id <task-id> --file-name <obs-path-without-bucket>
238```
239
240- **SDK:** `client.get_task_preview(task_id, file_name)`
241- **API:** `GET /v1/data-eng/proc-tasks/{task_id}/preview?file_name=<file_name>`
242
243#### Get task frames
244
245Query directory file list of task input/output datasets. `prefix` = dataset OBS path excluding bucket name (e.g., `cloudrobo/f91cee72-.../1ddf1498-.../`).
246
247```bash
248cloudrobo dataset proc get-frames --task-id <task-id> --prefix <obs-path-without-bucket>
249```
250
251- **SDK:** `client.get_task_frames(task_id, prefix)`
252- **API:** `GET /v1/data-eng/proc-tasks/{task_id}/frames?prefix=<prefix>`
253
254### Evaluation Tasks (eval-tasks)
255
256Evaluation tasks differ from processing tasks in field names, deletion granularity, and supported
257operations. See the full comparison table in `references/task-config-catalog.md`.
258
259#### Create an evaluation task
260
261```bash
262cloudrobo dataset eval create-task --name <task-name> --task-config '<json-config>' [--workspace-id <id>] [--wait] [--timeout 1800]
263```
264
265- **SDK:** `client.create_eval_task(task_config: dict)`
266- **API:** `POST /v1/data-eng/eval-tasks`
267
268**task-config field description**:
269
270The eval-task task-config requires **two sets of dataset fields**: top-level single-value fields (`dataset_type`, `dataset_id`, `dataset_name`, `dataset_path`) + `dataset_configs` array (single dataset, format same as proc-task).
271
272Required fields: `name`, `algo_type`, `algo_id`, `algo_name`, `algo_entrance`, `image`, `catalog_id` (workspace's), `cluster_type`, `task_framework_type`, `dataset_type`/`dataset_id`/`dataset_name`/`dataset_path` (top-level), `dataset_configs`, `robot_config`, `resource_pool_type`, `head_spec`, `worker_spec`, `worker_num`, `evs_spec`, `output_type`, `output_path`, `output_name`.
273
274Optional: `description`, `resource_id`, `dedicated_pool_name`.
275
276**⚠️ Key reminders**:
277- Both top-level dataset fields and `dataset_configs` array required
278- `dataset_name` cannot be empty (extract from OBS path last directory for UDF_OBS_ASSET)
279- `dataset_type` values: `BUILD_IN_ASSET` / `UDF_OBS_ASSET`
280
281See `references/task-config-catalog.md` for full field mapping and eval-task field differences.
282
283#### List evaluation tasks
284
285```bash
286cloudrobo dataset eval list-tasks [--status <status>] [--name <name>] [--workspace-id <id>]
287```
288
289- **SDK:** `client.list_eval_tasks(workspace_id=None, **params)`
290- **API:** `GET /v1/data-eng/eval-tasks?workspace_id=<id>`
291
292#### Show evaluation task detail
293
294```bash
295cloudrobo dataset eval show-task --task-id <task-id>
296```
297
298- **SDK:** `client.get_eval_task_detail(task_id)`
299- **API:** `GET /v1/data-eng/eval-tasks/{task_id}`
300
301#### Update an evaluation task (SDK only)
302
303- **SDK:** `client.update_eval_task(task_id, task_config: dict)`
304- **API:** `PATCH /v1/data-eng/eval-tasks/{task_id}`
305
306#### Delete an evaluation task (single granularity, SDK only)
307
308- **SDK:** `client.delete_eval_task(task_id)`
309- **API:** `DELETE /v1/data-eng/eval-tasks/{task_id}`
310
311**Note:** eval-tasks deletion is single-task granularity (`delete-task`), same as proc-tasks
312(`delete-task`). eval-tasks do not support restart.
313
314#### Retrieve evaluation task logs
315
316```bash
317# Step 1: List log files
318cloudrobo dataset eval get-log --task-id <id> --is-system true
319cloudrobo dataset eval get-log --task-id <id> --is-system false
320
321# Step 2: Get log content
322cloudrobo dataset eval get-log --task-id <id> --file-name <name> --file-path <path>
323```
324
325- **SDK:** `client.list_eval_log_files(task_id, is_system=True)` + `client.get_eval_task_log(task_id, file_name, ...)`
326- **API:**
327  - `GET /v1/data-eng/eval-tasks/{task_id}/logs?is_system=true|false`
328  - `GET /v1/data-eng/eval-tasks/{task_id}/logs/{file_name}?file_path=&job_id=`
329
330#### Get evaluation task preview
331
332`file_name` is the OBS path of the report file (excluding bucket name). Extract from task detail's `target_report_path` by removing `obs://<bucket-name>/` prefix.
333
334For example: if `target_report_path` is `obs://cloudrobo-test-203/eval_task/report/abc-123/diversity_evaluation_report.pdf`, then `file_name` = `eval_task/report/abc-123/diversity_evaluation_report.pdf`.
335
336```bash
337cloudrobo dataset eval get-preview --task-id <task-id> --file-name <obs-path-without-bucket> [--is-download]
338```
339
340- **SDK:** `client.get_eval_task_preview(task_id, file_name, is_download=False)`
341- **API:** `GET /v1/data-eng/eval-tasks/{task_id}/preview?file_name=<obs-path-without-bucket>&isDownload=`
342
343Returns OBS temporary URL. Use `--is-download` for download link, omit for preview link. Save or download promptly.
344
345### Algorithm Discovery
346
347#### List available algorithms
348
349```bash
350cloudrobo asset list-publication-assets --type algorithm --tags "Data Processing" [--name <fuzzy-name>] [--limit 20]
351```
352
353- **SDK (cross-package):** `asset_client.list_publication_assets(type="algorithm", sub_type="data_processing", limit=20)`
354- **API:** Cross-package — calls the asset service, not the dataset service directly.
355
356Each algorithm includes `ext_metadata` with `engine.image_url`, `command`, and
357`environment_variables` needed for task creation. Use `--tags "Data Evaluation"` to discover
358evaluation algorithms.
359
360## Reference Documents
361
362- [CLI Installation Guide](references/cli-installation-guide.md) — cloudrobo CLI installation and configuration
363- [IAM Policies](references/iam-policies.md) — Least-privilege credential model
364- [Verification Method](references/verification-method.md) — Verification method details
365- [Dataflow Diagram](references/dataflow-diagram.md) — Mermaid data flow diagram
366- [Acceptance Criteria](references/acceptance-criteria.md) — Acceptance criteria
367- [Task Config Reference](references/task-config-catalog.md) — Algorithm field mapping, required fields template, envs format, eval-tasks field differences
368- [Interactive Workflow](references/interactive-workflow.md) — Detailed step-by-step interactive creation workflows for proc-tasks and eval-tasks
369
370## Edge Cases
371
372| Scenario | Handling |
373|----------|----------|
374| Missing `workspace_id` | Run `cloudrobo workspace use` or use `--workspace-id` |
375| Task in non-terminal state | `wait-task` polls until SUCCEEDED/FAILED/DELETED or timeout |
376| Log file not found | Falls back to `system-std-output.log` / `job-std-output.log` |
377| Large log file | Default 64KB tail; use `--all` or `download-log` |
378| Task creation fails | Check algo_type, JSON validity, dataset_configs, resource quota |
379| AK/SK not set | Set `HUAWEI_CLOUD_AK`/`HUAWEI_CLOUD_SK` |
380| Algorithm not found | Use `--name` fuzzy search or `sub_type` filter |
381| eval-task delete | Single delete only; no batch, no restart |
382| Pipeline input | Wrap `target_path` into `dataset_configs` entry |
383| Evaluation report link | OBS temp URL; save/download promptly |
384| `envs` format | JSON array string, not object; see task-config-catalog.md |
385| `catalog_id` mismatch | Use workspace's, not algorithm's |
386| `list-assets` params | Provide `--catalog-id` or `--repository-id`; get from `cloudrobo workspace current` |
387| Algorithm source | Built-in: `list-publication-assets`; custom: `list-assets` |
388| `dataset_configs` | Use asset's `url` field; don't manually concatenate |
389| Log query | Get file list first for `file_path`, then fetch content |
390| Task states | Terminal: SUCCEEDED, FAILED, DELETED; non-terminal: CREATING, RUNNING, PENDING, FROZEN |
391| Task deletion | Irreversible |
392| Algorithm fields | Extract from `ext_metadata`; don't fabricate |
393| Object storage | Must use `obs://`; `s3://` prohibited |
394| API paths | From SDK `_url()` calls, not inferred |
395| Cross-skill | No training/inference; use cloudrobo-train/infer |
396| Mutating ops | create/update/delete/restart require confirmation |
397| Workflow triggers | No params → interactive; complete params → skip to confirm |
398| Missing optional fields | Skip if no `environment_variables`; use defaults for `worker_spec`; prompt for `robot_config` in eval |
399| Empty field validation | Except `description`, all params must be non-empty; SDK rejects empty strings/None/empty dicts before submission |
400| `head_spec`/`worker_spec` | Must include `cpu`, `memory`, `gpu`, `npu` keys (value `0` is valid) |
401| `dataset_configs` empty | Must contain at least 1 dataset entry; empty array `"[]"` is invalid |
402| Advanced resources | DEDICATED_POOL: query for IDs; Ray: pair cluster/framework types, non-zero head_spec |
403
404## Verification Method
405
406### Specification Compliance Verification
407
408```bash
409bash scripts/test-cli-commands.sh -s . -e cli
410```
411
412### Functional Testing
413
414```bash
415# CLI / SDK
416bash scripts/test-cli-commands.sh -s . -e {cli|sdk}
417```
418
419API-level verification is manual — replay the API paths in
420`references/task-config-catalog.md` in
421[API Explorer](https://console.huaweicloud.com/apiexplorer/).
422
423### Test Cases
424
425See `templates/test-vars.json` for the full test case list covering proc-tasks, eval-tasks,
426algorithm discovery, and pipeline scenarios.
427
428### Verification Checklist
429
430- After creating a task, poll status (recommended 15s interval), report each state change to user
431- On SUCCEEDED: verify output via `get-preview`, output system log
432- On FAILED: ask user whether to view logs, fetch system and job logs per the two-step flow
433  (list files → get content)
434- For pipeline: verify processing `target_path` is wrapped into `dataset_configs` for the eval task, then eval
435  SUCCEEDED → get-preview returns OBS link
436- For eval tasks: verify report preview after SUCCEEDED
437
438## Best Practices
439
440- Always run `list-algorithms` first to discover available operators before creating a task
441- Use `--dry-run` with `create-task` to validate task config before actual execution
442- Use `wait-task` with `--timeout` to avoid indefinite polling; report each status transition
443- On task failure, retrieve both system logs (`--is-system true`) and job logs (`--is-system false`),
444  analyze error patterns (OOM / path not found / image pull failure / OBS access) and suggest fixes
445  before restarting
446- For pipeline orchestration, wait for processing SUCCEEDED before creating evaluation task
447- Before batch delete, confirm task IDs to avoid irreversible deletion
448- Clean up completed/failed tasks with `delete-task` to free resources
449- Set `CLOUDROBO_DEBUG=1` for verbose error output during troubleshooting
450- Evaluation report links are OBS temporary URLs — save or download promptly

  huaweicloud/huaweicloud-skills/tree/main/skills/ai/cloudrobo/huawei-cloud-cloudrobo-dataset commit 2b380dc2bc 
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  Frequently asked questions
     
 Run npx skillmds@latest add huaweicloud/huawei-cloud-cloudrobo-dataset in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.
 
   
 Manage CloudRobo data processing (proc-tasks) and data evaluation (eval-tasks) — query algorithms, create/list/show/update/delete/restart tasks; poll task status until terminal; retrieve system and job logs; download logs; preview output data and frames; discover available algorithms from the asset marketplace; orchestrate processing→evaluation pipelines; batch-manage tasks across workspaces; diagnose failures via log analysis. Triggers include: data processing task management, data evaluation task management, task status polling, log retrieval for troubleshooting, output data preview, algorithm discovery, task pipeline orchestration, batch task management, failure diagnosis, dataset, proc-tasks, eval-tasks. It is listed under Product & Planning on SkillMD.
 
   
 This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.
 
   
 This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.
 
   
 Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.
 
   
 huaweicloud (@huaweicloud) published this skill. Their other Agent Skills are listed on their SkillMD profile.

   npx skillmds@latest add huaweicloud/huawei-cloud-cloudrobo-dataset

Huawei Cloud Cloudrobo Dataset

File contents

Overview

Prerequisites

Workflow

Interactive Task Creation

Task Polling and Result Handling

Pipeline Workflow (Task Orchestration)

Batch Workflow (Batch Tasks)

Diagnosis Workflow (Failure Diagnosis)

Analytics Workflow (Data Analysis)

Long-Running Task Workflow

CLI Command Format Standard

Core Commands

Task Management (proc-tasks)

Create a data processing task

List tasks

Show task detail

Update a task (SDK only)

Delete tasks (SDK only)

Restart a task

Task Monitoring

Wait for task to reach terminal state

Retrieve task logs

Download a log file

Get task resource usage

Data Preview

Preview task output data

Get task frames

Evaluation Tasks (eval-tasks)

Create an evaluation task

List evaluation tasks

Show evaluation task detail

Update an evaluation task (SDK only)

Delete an evaluation task (single granularity, SDK only)

Retrieve evaluation task logs

Get evaluation task preview

Algorithm Discovery

List available algorithms

Reference Documents

Edge Cases

Verification Method

Specification Compliance Verification

Functional Testing

Test Cases

Verification Checklist

Best Practices

Related skills

Frequently asked questions

How do I install the Huawei Cloud Cloudrobo Dataset skill?

What does the Huawei Cloud Cloudrobo Dataset skill do?

Is Huawei Cloud Cloudrobo Dataset safe to use?

Which AI agents work with Huawei Cloud Cloudrobo Dataset?

Is Huawei Cloud Cloudrobo Dataset free to use?

Who published Huawei Cloud Cloudrobo Dataset?