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ac-knowledge-graph

Manage knowledge graph for autonomous coding. Use when storing relationships, querying connected knowledge, building project understanding, or maintaining semantic memory.

54

Quality

60%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./.claude/skills/ac-knowledge-graph/SKILL.md

The canonical home for this skill is ac-knowledge-graph in fernandezbaptiste/Skrillz

SKILL.md
Quality
Evals
Security

Quality

Content

58%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 is concise and well-structured with clean one-level disclosure, but its Quick Start is not copy-paste runnable and it lacks any sequenced workflow or validation guidance for a stateful, disk-persisting skill.

Suggestions

Make the Quick Start fully executable: import Path, define project_dir, call `await graph.initialize()` before mutations, and show a complete runnable snippet.

Add a short sequenced workflow (initialize -> add entities/relations -> query -> verify persisted file) with a validation checkpoint confirming the graph file was written.

Surface a few key API methods inline in the API Reference section rather than only pointing to the source file.

DimensionReasoningScore

Conciseness

The body is lean with no concept re-explanation, but the single-sentence 'Purpose' section largely restates the frontmatter description, a minor redundancy that keeps it just below score 5.

4 / 5

Actionability

The Quick Start shows real code but it is incomplete — `project_dir` is undefined, `initialize()` is never called, and the API Reference offers no method surface inline, only a pointer to the source file.

3 / 5

Workflow Clarity

Only isolated API calls are shown with no initialize -> mutate -> persist -> query sequence and no validation checkpoints, despite the skill persisting to disk on every mutation.

2 / 5

Progressive Disclosure

A short, well-sectioned overview points one level deep to `scripts/knowledge_graph.py` with the reference clearly signaled, appropriate for a sub-50-line skill with a single bundle file.

5 / 5

Total

14

/

20

Passed

Description

62%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.

The description clearly states both capability and use-conditions with relevant trigger terms, placing it solidly above average. It could reach the top anchor by replacing abstract gerunds with concrete, user-voiced trigger phrases and adding synonym coverage.

DimensionReasoningScore

Specificity

Names the knowledge-graph domain with several action gerunds ('storing relationships', 'querying connected knowledge', 'building project understanding') but these are abstract rather than the comprehensive concrete actions of score 5.

3 / 5

Completeness

Both 'what' ('Manage knowledge graph for autonomous coding') and 'when' ('Use when storing relationships, querying connected knowledge...') are explicit, but the 'when' uses activity gerunds rather than user-named trigger phrases, falling just short of score 5.

4 / 5

Trigger Term Quality

Relevant natural terms like 'knowledge graph', 'relationships', and 'semantic memory' appear, but common synonyms and variations a user would say are missing.

3 / 5

Distinctiveness Conflict Risk

'Knowledge graph for autonomous coding' and 'semantic memory' carve a mostly distinct niche with only minor overlap risk against a generic memory or notes skill.

4 / 5

Total

14

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
fernandezbaptiste/Skrillz
Reviewed

Table of Contents

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