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route-by-query-shape

When the agent calls memory_search with a relationship-shaped query ("who did I talk to about X"), redirect to the knowledge_graph backend where it will actually find the answer.

68

Quality

83%

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

78%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 lean, well-organized body for a simple built-in interceptor skill with excellent token efficiency and structure. Its main weakness is actionability: it documents what the interceptor does and where it lives, but omits activation and verification details that would make the guidance complete.

Suggestions

Add a short note on how the interceptor is activated or toggled (frontmatter shows always: false, but the body never explains what enables it) so readers know when it will actually be in effect.

Include a quick way to verify the re-route is working (e.g., an example memory_search call and the expected backend it lands on) to close the actionability gap.

Document the fallback behavior when the graph backend also misses, or when the relationship-shape detection misfires, so the pipeline has an explicit checkpoint.

DimensionReasoningScore

Conciseness

The body is ~150 words with zero padding: it explains only the non-obvious why ("the answer lives in entity relationships, not in chunk text") and the observable behavior change. Every token earns its place.

5 / 5

Actionability

Concrete details exist (the interceptor file path, "fires up to 12 times per session", and the watch→detect→extract→re-route mechanism), but there is no executable guidance and key operational details are missing — e.g., how the interceptor is activated given always: false, or how to verify it fired. Not 4 because nothing here is copy-paste executable; not 2 because the mechanism and implementation location are specifically stated.

3 / 5

Workflow Clarity

The single purpose (re-route relationship queries to the graph backend) is unambiguous and the internal pipeline is clearly sequenced in prose. It stops short of 5 because there is no checkpoint or fallback guidance for misfires (e.g., what happens when detection is wrong), though no destructive/batch cap applies.

4 / 5

Progressive Disclosure

The skill is well under 50 lines, has no bundle files, and needs none: the three short sections (intro, What you'll see, Implementation) are well-organized with no nested or buried references, matching the simple-skill exception for a 5.

5 / 5

Total

17

/

20

Passed

Description

87%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: it states what the skill does, when it applies, and includes a concrete natural-language trigger example, all in one concise sentence. Minor room to grow only in covering synonym phrasings of relationship questions.

DimensionReasoningScore

Specificity

The description names concrete actions — intercepting "memory_search with a relationship-shaped query" and redirecting "to the knowledge_graph backend" — backed by a quoted example query. It is more precise than the 3 anchor's 1-2 generic actions, but does not enumerate the full detection/extraction behavior needed for a 5.

4 / 5

Completeness

It explicitly answers both: what ("redirect to the knowledge_graph backend where it will actually find the answer") and when ("When the agent calls memory_search with a relationship-shaped query") with a concrete quoted trigger phrase. The missing-'Use when' cap does not apply since explicit trigger guidance is present.

5 / 5

Trigger Term Quality

"who did I talk to about X" is a genuinely natural user phrase and "relationship-shaped query" frames the trigger well. It falls short of 5 because common variations (e.g., "who worked with me on") and synonyms are absent.

4 / 5

Distinctiveness Conflict Risk

A clear niche — routing relationship-shaped memory_search queries to the knowledge graph backend — with distinct, specific triggers that would not plausibly fire for unrelated skills.

5 / 5

Total

18

/

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
Bitterbot-AI/bitterbot-desktop
Reviewed

Table of Contents

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