How do I install the Forecast Diagnostics skill?

Run npx skillmds@latest add aws-samples/forecast-diagnostics 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.

Is Forecast Diagnostics safe to use?

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Which AI agents work with Forecast Diagnostics?

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.

Is Forecast Diagnostics free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Forecast Diagnostics?

aws-samples (@aws-samples) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Forecast Diagnostics by aws-samples

Name: Forecast Diagnostics
Author: aws-samples

Forecast Diagnostics

Use this skill to investigate and troubleshoot Amazon Forecast problems by analyzing dataset import, predictor training, forecast generation, accuracy metrics, what-if analysis, explainability, auto-predictor, and following structured runbooks. Activate when: dataset import failures, predictor training errors, forecast generation issues, poor accuracy, what-if analysis problems, explainability errors, or the user says something is wrong with Forecast without naming specific symptoms.

aws-samples 4e9c8aa 17 files · 84.0 KB Updated Sep 17, 2026

File contents

Amazon Forecast Diagnostics

When to use

Any Amazon Forecast investigation where the console alone is insufficient — dataset management, predictor training, forecast generation, accuracy evaluation, what-if analysis, or explainability.

Investigation workflow

Step 1 — Collect and triage

aws forecast list-dataset-groups
aws forecast list-predictors
aws forecast list-forecasts
aws forecast list-what-if-analyses

Step 2 — Domain deep dive

aws forecast describe-dataset-group --dataset-group-arn <arn>
aws forecast describe-auto-predictor --predictor-arn <arn>
aws forecast describe-forecast --forecast-arn <arn>
aws forecast get-accuracy-metrics --predictor-arn <arn>

Step 3 — Detailed investigation

aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventSource,AttributeValue=forecast.amazonaws.com --max-results 20
aws forecast describe-dataset-import-job --dataset-import-job-arn <arn>

Read references/guardrails.md before concluding on any Forecast issue.

Tool quick reference

Tool / API	When to use
`forecast list-dataset-groups`	List dataset groups
`forecast describe-auto-predictor`	Check predictor status
`forecast describe-forecast`	Check forecast status
`forecast get-accuracy-metrics`	Get predictor accuracy
`forecastquery query-forecast`	Query forecast values
`forecast list-what-if-analyses`	List what-if analyses
`forecast list-explainabilities`	List explainability jobs

Gotchas: Amazon Forecast

Dataset import requires specific CSV format with timestamp, target value, and item ID columns.
AutoPredictor is recommended over legacy predictors. It automatically selects best algorithm.
Predictor training can take hours. Training creates an immutable predictor.
Forecast generation is separate from training. Must create forecast from predictor.
Accuracy metrics (WAPE, RMSE, MASE) are available after training. Lower WAPE is better.
What-if analysis requires an existing forecast. It models scenarios with modified data.
Explainability shows feature importance. Requires predictor with explainability enabled.
Forecast horizon must match predictor's forecast horizon setting.

Anti-hallucination rules

Always cite specific ARNs, job IDs, or API responses as evidence.
Training takes hours. Never assume immediate predictor availability.
Forecast generation is separate from training. Never assume automatic forecast.
AutoPredictor is recommended. Never default to legacy predictor APIs.
Accuracy metrics are predictor-specific. Never assume universal accuracy.
Spend no more than 2 minutes on any single hypothesis. Pivot if inconclusive.

14 runbooks

Category	IDs	Covers
A — Datasets	A1-A2	Dataset import, data format
B — Predictors	B1-B3	Predictor training, AutoPredictor, accuracy
C — Forecasts	C1-C2	Forecast generation, forecast query
D — What-If	D1-D2	What-if analysis, what-if forecast
E — Explainability	E1	Explainability analysis
F — Data Quality	F1-F2	Time series quality, missing values
Z — Catch-All	Z1	General troubleshooting

---name: forecast-diagnosticsdescription: Use this skill to investigate and troubleshoot Amazon Forecast problems by analyzing dataset import, predictor training, forecast generation, accuracy metrics, what-if analysis, explainability, auto-predictor, and following structured runbooks. Activate when: dataset import failures, predictor training errors, forecast generation issues, poor accuracy, what-if analysis problems, explainability errors, or the user says something is wrong with Forecast without naming specific symptoms.---# Amazon Forecast Diagnostics## When to useAny Amazon Forecast investigation where the console alone is insufficient — dataset management, predictor training, forecast generation, accuracy evaluation, what-if analysis, or explainability.## Investigation workflow### Step 1 — Collect and triage```aws forecast list-dataset-groupsaws forecast list-predictorsaws forecast list-forecastsaws forecast list-what-if-analyses```### Step 2 — Domain deep dive```aws forecast describe-dataset-group --dataset-group-arn <arn>aws forecast describe-auto-predictor --predictor-arn <arn>aws forecast describe-forecast --forecast-arn <arn>aws forecast get-accuracy-metrics --predictor-arn <arn>```### Step 3 — Detailed investigation```aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventSource,AttributeValue=forecast.amazonaws.com --max-results 20aws forecast describe-dataset-import-job --dataset-import-job-arn <arn>```Read `references/guardrails.md` before concluding on any Forecast issue.## Tool quick reference| Tool / API | When to use ||------------|-------------|| `forecast list-dataset-groups` | List dataset groups || `forecast describe-auto-predictor` | Check predictor status || `forecast describe-forecast` | Check forecast status || `forecast get-accuracy-metrics` | Get predictor accuracy || `forecastquery query-forecast` | Query forecast values || `forecast list-what-if-analyses` | List what-if analyses || `forecast list-explainabilities` | List explainability jobs |## Gotchas: Amazon Forecast- Dataset import requires specific CSV format with timestamp, target value, and item ID columns.- AutoPredictor is recommended over legacy predictors. It automatically selects best algorithm.- Predictor training can take hours. Training creates an immutable predictor.- Forecast generation is separate from training. Must create forecast from predictor.- Accuracy metrics (WAPE, RMSE, MASE) are available after training. Lower WAPE is better.- What-if analysis requires an existing forecast. It models scenarios with modified data.- Explainability shows feature importance. Requires predictor with explainability enabled.- Forecast horizon must match predictor's forecast horizon setting.## Anti-hallucination rules1. Always cite specific ARNs, job IDs, or API responses as evidence.2. Training takes hours. Never assume immediate predictor availability.3. Forecast generation is separate from training. Never assume automatic forecast.4. AutoPredictor is recommended. Never default to legacy predictor APIs.5. Accuracy metrics are predictor-specific. Never assume universal accuracy.6. Spend no more than 2 minutes on any single hypothesis. Pivot if inconclusive.## 14 runbooks| Category | IDs | Covers ||----------|-----|--------|| A — Datasets | A1-A2 | Dataset import, data format || B — Predictors | B1-B3 | Predictor training, AutoPredictor, accuracy || C — Forecasts | C1-C2 | Forecast generation, forecast query || D — What-If | D1-D2 | What-if analysis, what-if forecast || E — Explainability | E1 | Explainability analysis || F — Data Quality | F1-F2 | Time series quality, missing values || Z — Catch-All | Z1 | General troubleshooting |

Frequently asked questions