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facts-discover

Scan the codebase and classify every fact by lifecycle stage — tag @draft, @spec, or @implemented based on what the code actually shows. Add missing facts, fix inaccurate ones, remove obsolete ones. Use when asked to discover facts, bootstrap or update a fact sheet, scan the codebase for truths, sync facts to match the code, or audit the fact sheet for accuracy.

72

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

75%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 highly actionable, well-sequenced skill body with excellent concrete command examples and validation checkpoints at both ends of the workflow. Its main weakness is repetition — three core principles are each restated multiple times across Steps 3b/4 and the Guidelines section, inflating the token budget by roughly a third.

Suggestions

Consolidate the command-quality principle into one authoritative statement (keep the Step 3b falsifiability test and the good/bad examples) and drop its restatements in Guidelines — the 'add/remove commands' guidance repeats nearly verbatim.

Merge the behavioral-over-structural guidance from Steps 2 and 4 and the Guidelines into a single prioritized list, keeping the good/bad `facts add` examples once.

Add an explicit feedback loop to Step 6: if `facts check` fails after edits, revisit the commands added in Step 3b and fix or revert them before reporting.

DimensionReasoningScore

Conciseness

Mostly efficient and domain-specific, but three core principles are each restated ~3 times: command falsifiability (Step 3b blockquote, Guidelines "Command quality matters more than command count" and "Only add commands that would break"), behavioral-over-structural facts (Steps 2, 4, Guidelines), and domain vocabulary consistency (Steps 2b, 3, 4, Guidelines). This goes beyond minor trimming and the body could be tightened to ~200 lines without loss.

3 / 5

Actionability

Fully executable throughout: exact CLI commands (`facts list`, `facts edit <id> --add-tag "implemented"`, `facts remove <id>`, `facts add "..." --section`), concrete good/bad shell command examples for both facts and validation commands, and a complete worked example session covering the common cases.

5 / 5

Workflow Clarity

A clearly sequenced process (1, 2, 2b, 3, 3b, 4, 5, 6) with validation at both ends (`facts check` in Step 1 and Step 6) and per-case error handling (partial truths, obsolete facts, failed commands). Minor gap: no explicit recovery loop for the final validation — Step 6 says to confirm checks pass but not what to do if one fails.

4 / 5

Progressive Disclosure

Good single-file structure with well-organized, clearly headed sections and no buried or nested references (no bundle files exist). The ~90 lines of good/bad command examples in Step 3b are central guidance rather than clearly-separable reference material, but at ~310 lines the body is on the large side for one file.

4 / 5

Total

16

/

20

Passed

Description

100%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.

An exemplary description: concrete third-person actions, an explicit and comprehensive trigger clause, and a distinct niche with minimal conflict risk. It reads like the rubric's own good examples.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "classify every fact by lifecycle stage — tag @draft, @spec, or @implemented", "Add missing facts, fix inaccurate ones, remove obsolete ones" — comprehensively covering the fact-sheet maintenance workflow in third-person voice.

5 / 5

Completeness

Both questions are answered explicitly and concretely: the "what" is the scan/classify/tag/add/fix/remove workflow, and the "when" is an explicit trigger clause listing concrete user requests.

5 / 5

Trigger Term Quality

The "Use when" clause covers a comprehensive set of natural phrasings users would say: "discover facts", "bootstrap or update a fact sheet", "scan the codebase for truths", "sync facts to match the code", "audit the fact sheet for accuracy" — synonyms and variations are well covered.

5 / 5

Distinctiveness Conflict Risk

A clear niche (fact sheet lifecycle classification and syncing) with distinct, domain-specific triggers ("fact sheet", "sync facts", "audit the fact sheet") that are unlikely to fire for unrelated skills.

5 / 5

Total

20

/

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
av/harbor
Reviewed

Table of Contents

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