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knowledge-graph

Three-Layer Memory System — automatic fact extraction, entity-based knowledge graph, and weekly synthesis. Manages life/areas/ entities with atomic facts and living summaries.

52

Quality

58%

Does it follow best practices?

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tessl review fix ./clawdbot/knowledge-graph/SKILL.md

The canonical home for this skill is knowledge-graph in jdrhyne/agent-skills

SKILL.md
Quality
Evals
Security

Quality

Content

57%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 well-structured and highly actionable with executable code and concrete schemas, but it is monolithic for its size, repeats the recall policy across sections, and lacks explicit validation checkpoints for its batch cron workflows. Strong on actionability, weaker on conciseness and workflow validation.

Suggestions

Add an explicit validation step to the fact-extraction and weekly-synthesis workflows (e.g., 'verify facts.jsonl is valid JSONL and IDs are unique after append') with a fix-and-retry loop to lift workflow clarity above the batch-operation cap.

Move detailed setup/cron-config and recall-policy material into reference files (e.g., SETUP.md, RECALL.md) and link to them from the overview to improve progressive disclosure and reduce repetition.

Cut restated content — the 'Why This Matters' bullets and the 'Every conversation makes your agent smarter' flywheel line duplicate the rules above them and add token weight without new guidance.

DimensionReasoningScore

Conciseness

Mostly efficient and actionable, but contains repetition (the Low-token Recall Policy is restated in Rules, then 'Why This Matters', then the AGENTS.md and HEARTBEAT.md snippets) and marketing fluff ('Every conversation makes your agent smarter. Facts compound. Summaries stay fresh.'). Matches 'mostly efficient but includes some unnecessary explanation or could be tightened'.

3 / 5

Actionability

Provides copy-paste-ready bash (mkdir/echo/cat), concrete JSONL fact objects, yaml cron configs, and markdown blocks for AGENTS.md/HEARTBEAT.md. The cron task workflows themselves are numbered natural-language steps rather than runnable scripts, which is the minor gap keeping it from a 5.

4 / 5

Workflow Clarity

Tasks are clearly sequenced with built-in safety (skip-if-known, supersede-if-contradicts), but fact extraction and weekly synthesis are batch/destructive-ish operations with no explicit validation/verification checkpoint or fix-and-retry feedback loop, so the batch-operation cap of 3 applies. Not a 2 because the sequence is well-defined; not a 4 because no output verification step exists.

3 / 5

Progressive Disclosure

Well-organized with clear section headers, but it is a ~250-line monolithic file with no bundle/reference files splitting out detailed material (setup, cron configs, recall policy), and the 'simple skill under 50 lines' exception does not apply. Matches 'some structure but content that should be separate is inline'.

3 / 5

Total

13

/

20

Passed

Description

58%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 communicates a clear, specific capability set but omits any explicit 'when to use' trigger guidance, capping completeness at 3, and leans on technical jargon over natural user phrases. It is distinct and reasonably specific but would benefit from trigger phrases.

Suggestions

Add an explicit 'Use when...' clause listing natural triggers such as 'when the user says remember that, asks what we know about a person/company/project, or mentions tracking facts about entities'.

Include natural synonyms users actually say ('remember', 'recall', 'people', 'companies') rather than only technical terms like 'atomic facts' and 'living summaries'.

Tighten 'entity-based knowledge graph' and 'living summaries' into more concrete action language to push specificity toward a 5.

DimensionReasoningScore

Specificity

Lists several concrete actions — 'automatic fact extraction', 'entity-based knowledge graph', 'weekly synthesis', 'Manages life/areas/ entities with atomic facts and living summaries' — which matches the 'several specific actions; minor gaps' anchor. Not a 3 because it names more than 1-2 actions; not a 5 because 'knowledge graph' and 'synthesis' are somewhat abstract versus the fully concrete anchor example.

4 / 5

Completeness

The 'what' is clear (extraction, graph, synthesis, entity management), but there is no 'Use when...' clause or equivalent explicit trigger guidance, which the rubric caps at 3. Not a 4 because 'when' is entirely absent rather than merely imprecise.

3 / 5

Trigger Term Quality

Relevant keywords like 'fact extraction' and 'knowledge graph' are present, but the description leans technical ('entity-based', 'atomic facts', 'living summaries') and omits the natural user phrases ('remember', 'what do we know about', people/companies) that appear in the body. Matches 'some relevant keywords but missing common variations or synonyms'.

3 / 5

Distinctiveness Conflict Risk

The 'Three-Layer Memory System' / 'life/areas/ entities' framing carves a fairly distinct niche with a specific directory layout, giving minor overlap risk with other memory skills. Not a 5 because 'memory system' still overlaps conceptually with generic memory skills and triggers are not sharply distinct.

4 / 5

Total

14

/

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository
bap-jorkim/agent-skills-fork-feb-25
Reviewed

Table of Contents

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