feat: Add ai-optimization skill for SageMaker AI Optimization APIs

[Lokiiiiii]

New skill covering the 14 SageMaker AI Optimization API operations (AIWorkloadConfig, AIBenchmarkJob, AIRecommendationJob) with guided workflows for benchmarking LLM inference and getting deployment recommendations.

Skill structure:

• SKILL.md (110 lines): Main skill with intent-matching description
• references/benchmark-workflow.md (96 lines): Benchmark job guide
• references/benchmark-results.md (78 lines): Results download code
• references/recommendation-workflow.md (96 lines): Recommendation guide
• references/recommendation-options.md (74 lines): Config options + dataset
• references/recommendation-deploy.md (41 lines): ModelPackage deployment
• references/interpreting-results.md (78 lines): Metrics presentation

All files conform to DESIGN_GUIDELINES.md limits (SKILL.md <300, references <100 lines each). Code samples verified against the public Smithy model.

Related

Changes

Acknowledgment

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[krokoko]

Benchmark polling loop has no post-loop status check — failed jobs silently proceed to results download

File: benchmark-workflow.md (polling block)

The benchmark polling loop breaks on Failed but has no status gate afterward. The SKILL.md workflow proceeds to "download results," which will fail with a confusing error when the tar.gz doesn't
exist. The recommendation workflow does handle this correctly — this is an asymmetry.

Fix: Add post-loop status handling matching the recommendation workflow:
if status == "Failed":
print(f"Benchmark failed: {resp.get('FailureReason', 'Unknown')}")
print("Fix the issue above and re-run the job.")
elif status == "Stopped":
print("Benchmark was stopped before completion.")
else:
print("Benchmark completed. Proceed to download results.")

[krokoko]

Polling loops have no timeout — potential infinite hang

Files: benchmark-workflow.md, recommendation-workflow.md

Both while True loops have no max duration. If a job enters an unexpected non-terminal state, the notebook cell hangs indefinitely. Add a MAX_WAIT_SECONDS guard (e.g., 3600s for benchmark, 7200s for recommendation).

[krokoko]

No error handling on S3 download and tar extraction

File: benchmark-results.md

s3.get_object() and tarfile.open() have no try/except. Users with wrong IAM permissions see raw AccessDenied tracebacks. A corrupted archive gives an opaque ReadError. Add try/except with actionable messages.

[krokoko]

Pandas marked "optional" but unconditionally used

File: benchmark-results.md, line 6

Comment says # optional, for tabular display but pd.DataFrame(...) is called unconditionally. Either remove the "optional" comment or add a fallback.

[krokoko]

sm client used without being defined in benchmark-results.md

File: benchmark-results.md, line 12

The code uses sm.describe_ai_benchmark_job(...) but sm = boto3.client("sagemaker") is never created in this code block. Either add the client creation or a comment noting it comes from a prior cell.