Results for “task-analysis”

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

Routes reverse engineering, exploitation, penetration testing, malware, mobile, firmware, browser automation, documentation, and security tasks to the appropriate specialist skill. Use when a task spans modules or the correct reverse-skill entrypoint is unclear.

`analysis-agent`/`task-agent`/`review-agent`: use when symptoms, logs, metrics, regressions, or incidents need cause analysis; skip when no diagnosis decision exists.

`analysis-agent`/`task-agent`/`review-agent`: primary-Skill-selected for races, locks, optimistic conflicts, or worker overlap; never task owner; skip without concurrency impact.

`analysis-agent`/`task-agent`/`review-agent`: primary-Skill-selected for logs, metrics, traces, alerts, SLI/SLO, or diagnostics; never task owner; skip without signal impact.

Use `analysis-agent` to create a Task DAG from an accepted source-backed Brief when 2+ tasks have dependencies, parallel value, integration, or release order. Skip single edits, accepted DAGs, and unanalysed requests.

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md. Identifying inconsistencies, duplications, ambiguities, and underspecified items.

Provides Gemini CLI delegation workflows for large-context analysis tasks, including English prompt formulation, execution flags, and safe result handling. Use when the user explicitly asks to use Gemini for a specific task such as broad codebase analysis or long-document processing. Triggers on "use gemini", "delegate to gemini", "run gemini cli", "ask gemini", "use gemini for this task".

Generates Gantt charts with task dependencies, critical path analysis, and resource allocation

Analyzes AWS ECS clusters, services, and tasks, including health, deployment status, task failures, capacity providers, and resource utilization, with parallel execution and anti-hallucination guardrails.

Task Decomposition

Automate gender detection and name analysis tasks using the Genderize API through Composio's Rube MCP integration.

Analyze candidate task nodes, dependencies, collisions, and critical path before a consumer accepts or rejects a final DAG.

Executes Python code iteratively via an MCP bridge to produce verified results for calculations, data analysis, and task decomposition.

Generate one high-value follow-up workflow proposal when MoonMind execution quality issues are detected in a run.

`analysis-agent`/`task-agent`/`review-agent`: use when latency, throughput, bundle, memory, CPU, query, rendering, or resource cost needs a budget; skip without performance risk.

`analysis-agent`/`task-agent`/`review-agent`: use when a service split affects ownership, deployment, scaling, isolation, contracts, or data; skip without a split decision.

research-synthesis

`analysis-agent`/`task-agent`/`review-agent`: use when uploads, object storage, streaming, MIME, scanning, access, retention, or cleanup changes; skip without file/storage impact.

`analysis-agent`/`task-agent`/`review-agent`: use for search relevance, freshness, analytical grain, metrics, or rebuilds; skip bounded source queries and operational telemetry.

Use with task-agent or review-agent for task-local cache scope, freshness, invalidation, and source-load risk. Do not use without a cache decision or as task owner.

Analyze datasets to answer defined questions through statistical methods, trend identification, hypothesis testing, and correlation analysis. Use when the user needs evidence-backed findings or decisions from data; use exploratory-data-analysis instead for open-ended first-pass profiling before questions are defined.

Use `analysis-agent` to analyze permissions, secrets, sensitive data, trust boundaries, and injection; `task-agent` to implement controls; and `review-agent` to assess evidence. Skip self-review and no-trust-impact work.

`analysis-agent`/`task-agent`/`review-agent`: use when repeated failure needs a new hypothesis or proof path; skip an initial failure with verified cause and a different action.

Answer any data question, scaling effort from a one-number lookup to a full stakeholder-ready analysis with a recommendation.

`analysis-agent`/`task-agent`: use when a use case coordinates authorization, domain work, transactions, or external effects; skip transport, storage, and rule-only work.

Analyse text complexity across quantitative, qualitative, and reader-task dimensions with scaffolding recommendations. Use when selecting texts, assessing readability, or planning reading support.

`analysis-agent`/`task-agent`/`review-agent`: use when fixtures, factories, seeds, isolation, cleanup, or sensitive test-data rules change; skip when test data is unaffected.

Orchestrates multi-agent workflows defined in YAML piece files, delegating tasks to team members and managing state transitions.