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self-awareness

Claude Science's own session database schema and SDK surface for introspection via host.query(). Load this when you need to query your own conversation history, token usage, cost accounting, execution log, or artifact metadata beyond what host.frames()/host.artifacts() provide — e.g. "how many tokens has this session used", "what was my last tool call", "list every file I've written", "where are messages stored", "what tables can I query", "inspect frames.context_data", or any time you're about to PRAGMA-probe the Claude Science metadata DB to discover its schema.

74

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

92%

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

A high-quality, executable schema reference with excellent actionability and no fluff. The main weakness is monolithic structure: the long per-table column listings would benefit from being split into clearly signaled reference files for progressive disclosure.

Suggestions

Move the per-table column enumerations (Queryable tables, Denied tables) into a reference file such as references/schema.md and keep SKILL.md as an overview pointing to it with a clearly signaled link.

Consider extracting the worked examples into references/examples.md so the main body stays a concise dialect + table-index overview.

DimensionReasoningScore

Conciseness

Dense, high-signal reference with no padding about concepts Claude already knows (no 'what is SQLite' or 'how libraries work'); every line is schema, constraint, or executable example. Length is justified by content density rather than verbosity.

3 / 3

Actionability

Provides fully executable SQL via the repl tool with real table and column names, plus four copy-paste-ready worked examples (token/cost accounting, recent cells, context-depth, artifact listing) and a concrete SDK-surface table mapping accessor to tool.

3 / 3

Workflow Clarity

The single action (run host.query) is unambiguous, with a clearly sequenced 'Dialect and limits' section encoding guardrails (scoping, caps, clipping, 5s timeout) and explicit introspection steps (PRAGMA table_info / sqlite_master) before querying.

3 / 3

Progressive Disclosure

Well-organized into clear sections, but the ~250-line body is monolithic — the per-table column enumerations (Queryable tables, Denied tables) are content that could be split into one-level-deep reference files, and no bundle references are signaled.

2 / 3

Total

11

/

12

Passed

Description

90%

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, specific description with explicit trigger guidance and good natural-language examples. The only weakness is second-person voice ('you need to', 'your own') in the trigger clause, which the rubric penalizes.

Suggestions

Rewrite the trigger clause in third person / impersonal voice to match the good examples, e.g. 'Load when querying conversation history, token usage, cost accounting, execution log, or artifact metadata beyond host.frames()/host.artifacts()'.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions ('query your own conversation history, token usage, cost accounting, execution log, or artifact metadata via host.query()'), but the phrasing 'Load this when you need to query your own conversation history' uses second-person voice ('you need to', 'your own'), which the rubric penalizes by reducing specificity by one level.

2 / 3

Completeness

Explicitly answers both what ('Claude Science's own session database schema and SDK surface for introspection via host.query()') and when ('Load this when you need to query...'), with an explicit 'Load this when' trigger clause and concrete examples.

3 / 3

Trigger Term Quality

Strong coverage of natural trigger phrases a user would actually say — 'how many tokens has this session used', 'what was my last tool call', 'list every file I've written', 'where are messages stored', 'what tables can I query' — alongside technical terms like 'PRAGMA-probe' and 'frames.context_data'.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear, narrow niche — introspection of Claude Science's own metadata DB via host.query() — with triggers unlikely to fire for any other skill.

3 / 3

Total

11

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

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