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workflow-from-chats

Extract durable working preferences from recent Cursor chats and convert them into skills, rules, or workflow docs. Use when asked to learn preferences, mine feedback, personalize workflows, or generate team/person-specific agent guidance.

69

Quality

85%

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SecuritybySnyk

Critical

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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.

An efficient, well-structured instruction-only skill: terse imperative guidance, concrete field-level specifications, confidence-gated workflow with a user-confirmation stop condition, and clean section organization. Its only weaknesses are the absence of a worked example and an output-verification feedback loop.

DimensionReasoningScore

Conciseness

The body is lean and imperative throughout ('Do not summarize chats; extract reusable workflow guidance', 'Filter anecdotes that will not help future tasks'), adds only guidance Claude would not infer, and pads nothing — every token earns its place, matching anchor 5.

5 / 5

Actionability

Concrete, specific guidance throughout: inventory fields (title/topic, parent conversation ID, completion state), atom fields (trigger, decision rule, quality bar, stop condition), explicit confidence tiers, and artifact-choice rules. Minor gaps — no worked example of a preference atom or a final output — keep it at anchor 4 rather than 5.

4 / 5

Workflow Clarity

Eight clearly numbered steps with validation checkpoints: confidence rating gates the flow, and the contradicted tier explicitly stops to ask the user before writing files. However, there is no feedback loop verifying drafted artifacts against evidence before writing, so it matches anchor 4 rather than anchor 5's explicit validate-fix-retry loop.

4 / 5

Progressive Disclosure

A ~47-line single-purpose skill with no bundle files (references/, scripts/, assets/ are all absent) and no need for external references; its sections (Scope, Workflow, Confidence, Artifact Choice, Output) are well-organized and short, which per the rubric's simple-skill guidance merits anchor 5.

5 / 5

Total

18

/

20

Passed

Description

83%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 with explicit what-and-when structure, natural trigger phrases, and a well-defined niche. It is specific and complete, with only minor gaps in keyword synonym coverage and slight overlap risk with general personalization skills.

DimensionReasoningScore

Specificity

Names the domain (recent Cursor chats) and several concrete actions — extracting durable working preferences and converting them into an enumerated set of artifacts (skills, rules, workflow docs) — with only minor coverage gaps, matching anchor 4. It is more concrete than anchor 3's 1-2 minimal actions but less comprehensive than anchor 5.

4 / 5

Completeness

It explicitly answers both questions: the 'what' (extract durable working preferences from recent Cursor chats and convert them into skills, rules, or workflow docs) and a 'Use when asked to...' clause with four concrete trigger phrases, exactly matching anchor 5. Anchor 4's caveat about a weakly explicit 'when' does not apply.

5 / 5

Trigger Term Quality

'learn preferences', 'mine feedback', 'personalize workflows', and 'generate team/person-specific agent guidance' are natural phrases users would say, giving good keyword coverage; a few common synonyms (e.g., 'remember my preferences') are missing, so it does not reach anchor 5.

4 / 5

Distinctiveness Conflict Risk

The Cursor-chat preference-mining niche is mostly distinct, but broad triggers like 'personalize workflows' and 'learn preferences' create minor overlap risk with memory/personalization skills, matching anchor 4 rather than anchor 5's minimal-conflict niche.

4 / 5

Total

17

/

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
cursor/plugins
Reviewed

Table of Contents

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