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structured-outputs

Use this skill when you need Claude to return structured JSON — data extraction, classification, form parsing, or any task needing machine-readable output.

Quality

85%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tight, highly actionable skill: executable code for all three techniques with a clear recommendation and a decision table. Main gaps are the repeated hardcoded model version, missing JSON-parse failure guidance for the prefill and system-prompt methods, and no offload of schema examples to a reference file.

Suggestions

Replace the three hardcoded 'claude-opus-4-6' model strings with a single variable or a placeholder note, since pinned versions go stale and are not in a deprecated/old-patterns section.

Add brief failure-handling for Methods 2 and 3 (e.g., what to do when json.loads fails on malformed output, such as retrying with a corrective message), which would also strengthen workflow clarity.

Move the 'Common Extraction Schemas' examples into a references/ file (e.g., SCHEMAS.md) linked from the body, keeping SKILL.md as a lean overview.

DimensionReasoningScore

Conciseness

Mostly lean and code-first with no padded concept explanations, but the hardcoded version string 'claude-opus-4-6' is repeated three times — time-sensitive version info outside any deprecated section, which the guidelines say should penalize conciseness. Efficient overall with minor instances that could be trimmed.

4 / 5

Actionability

All three methods are given as fully executable, copy-paste-ready Python with worked examples and expected return values (contact extraction, classification), covering the common cases. Matches the top anchor.

5 / 5

Workflow Clarity

Clear method ordering with an explicit recommendation ('Tool use (Recommended)'), a stated decision basis ('Choose based on complexity'), and a reliability/best-for quick reference table. Not a destructive or batch workflow so the validation cap does not apply, but explicit checkpoints are incomplete: Methods 2 and 3 call json.loads with no failure or retry guidance.

4 / 5

Progressive Disclosure

Well-organized single-file structure with clear section headers and no dangling references (no bundle files exist and the body links to none). It sits above the simple-skill threshold at ~135 lines, and content like the 'Common Extraction Schemas' section could be split into a reference file, keeping it at 'good structure; minor organization gaps'.

4 / 5

Total

17

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that explicitly states both capability and trigger conditions with concrete, natural keywords. Minor improvements possible: enumerate a few more concrete use cases instead of the generic catch-all, and sharpen terms that overlap with adjacent skills.

DimensionReasoningScore

Specificity

Names several concrete actions ('return structured JSON', 'data extraction, classification, form parsing'), but coverage partly relies on the generic catch-all 'any task needing machine-readable output' rather than a comprehensive concrete list, matching the 'several specific actions; minor gaps' anchor.

4 / 5

Completeness

Explicitly answers both what ('return structured JSON — data extraction, classification, form parsing, machine-readable output') and when ('Use this skill when you need Claude to return structured JSON...') with concrete trigger phrases. The when-clause is explicit and specific, so the 4 anchor's 'could be more explicit' caveat does not apply.

5 / 5

Trigger Term Quality

Good natural keyword coverage ('structured JSON', 'data extraction', 'classification', 'form parsing', 'machine-readable output'), but a few natural phrasings users would say are missing (e.g., 'JSON output', 'parse JSON'). Not comprehensive enough for the 5 anchor's synonym/extension coverage.

4 / 5

Distinctiveness Conflict Risk

Clear niche (machine-readable output from Claude) with mostly distinct triggers, but 'data extraction' and 'classification' are broad enough to create minor overlap risk with closely related extraction or classification skills.

4 / 5

Total

17

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

ProwlrBot/prowlr-marketplace

Path

external/anthropic-official/structured-outputs/SKILL.md

Reviewed

Table of Contents

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