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aps-doc-ingestion

Expert documentation generation for ingestion layers. Automatically detects connector types (REST API, Database, File, Streaming), documents authentication patterns, rate limiting strategies, and incremental load patterns. Use when documenting data source ingestion workflows.

55

Quality

61%

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SecuritybySnyk

High

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tessl review fix ./aps-doc-skills/ingestion/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

42%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.

The body's core assets — the mandatory codebase-access gate and the exact documentation templates — are genuinely valuable and concrete. However, the skill is bloated by generic connector-detection catalogs Claude already knows, gives no executable guidance on how to extract the required data from .dig/.yml files, and lacks validation steps to confirm the generated documentation contains only real extracted data. Everything lives in one monolithic file with no progressive disclosure.

Suggestions

Cut or drastically compress the 'Layer-Specific Intelligence' section: Claude already knows what OAuth, Kafka topics, or updated_at fields are — keep only the project-specific signals that identify each pattern in .dig/.yml configs (e.g., 'td_authentication_id implies the auth block', 'a + operator in the query implies incremental').

Add a validation step after documentation generation: re-open datasources.yml and the .dig workflows and verify every documented table name, incremental field, and schedule matches the configs, confirming no generic placeholders leaked through.

Move the parent-page and child-page templates into references/templates.md and reference them from SKILL.md, keeping the main file to the access gate, the detection signals, and navigation — cutting its size by more than half.

DimensionReasoningScore

Conciseness

The ~380-line body pads several sections with generic knowledge Claude already has — e.g. 'Detects: endpoint URLs... HTTP methods (GET, POST, PUT)', 'Kafka topics/consumer groups', 'updated_at, modified_at, created_at fields' — in repetitive Detects/Documents blocks, and the closing Summary repeats earlier content. Not a 1 because the template and codebase-access sections carry genuine, non-obvious value.

2 / 5

Actionability

The codebase-access gate is fully concrete (exact refusal message, 'Use Glob to verify files exist') and the documentation template is a copy-paste-ready exact structure, but the detection sections are descriptive rather than instructive — no commands or patterns for how to actually extract connector types, table names, or incremental fields from .dig/.yml files. This is the 'some concrete guidance but incomplete' anchor, not the 'minor gaps' level above.

3 / 5

Workflow Clarity

A real pre-flight sequence exists ('1. Ask for codebase path if not provided 2. Use Glob to verify files exist 3. STOP if cannot read files'), but there are no post-generation validation checkpoints — the 'NO generic placeholders. Only real, extracted data.' rule is stated yet never verified against the source configs, leaving the sequence with implicit rather than explicit checkpoints.

3 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent) and the full parent/child page templates plus detection matrices are inlined in one long SKILL.md. Section headers provide some structure, but content that clearly belongs in separate reference files (the two page templates) is inline, which is the 'some structure, should be separate' anchor rather than the 'mostly well-placed' one.

3 / 5

Total

11

/

20

Passed

Description

80%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: specific, action-oriented, third-person, with an explicit 'Use when' clause and a well-defined ingestion-documentation niche. The main gaps are narrow trigger coverage (no synonyms like ETL, connectors, or pipeline terms) and a single general trigger condition rather than concrete varied trigger phrases.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'Automatically detects connector types (REST API, Database, File, Streaming), documents authentication patterns, rate limiting strategies, and incremental load patterns' — with comprehensive coverage of the domain, matching the top anchor rather than the 'minor gaps' level below.

5 / 5

Completeness

Both 'what' (detects connector types, documents auth/rate-limiting/incremental patterns) and 'when' ('Use when documenting data source ingestion workflows') are explicitly present in third-person voice, but the 'when' is a single general condition rather than the concrete multi-phrase triggers of the top anchor.

4 / 5

Trigger Term Quality

'Use when documenting data source ingestion workflows' plus 'ingestion layers' and 'data source' give good natural keyword coverage, but common synonyms and variations (connectors, ETL, data pipelines, specific tool names) are missing, so it falls short of the comprehensive-synonyms anchor at 5.

4 / 5

Distinctiveness Conflict Risk

'Ingestion layers' and 'data source ingestion workflows' define a clear niche with distinct triggers and minimal conflict risk; only minor overlap with generic documentation skills keeps it below the top anchor.

4 / 5

Total

17

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
treasure-data/td-skills
Reviewed

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