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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.

75

Quality

92%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Critical

Do not install without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

85%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a well-structured, concise skill that clearly defines a multi-step workflow for extracting preferences from chat transcripts. Its main strength is the clear sequencing, confidence framework, and artifact decision tree. Its primary weakness is the lack of concrete examples—a sample preference atom, a sample output synthesis, or an example artifact would make the skill significantly more actionable.

Suggestions

Add a concrete example of a 'preference atom' showing what trigger, workflow step, decision rule, quality bar, stop condition, evidence, and confidence look like when filled in.

Include a brief example of the expected output synthesis format with sample data to make the output section fully actionable.

DimensionReasoningScore

Conciseness

The content is lean and efficient. Every section serves a purpose—scope, workflow steps, confidence levels, artifact choice, and output format. There's no unnecessary explanation of concepts Claude already knows, and no padding or filler text.

3 / 3

Actionability

The workflow steps are clearly listed and specific markers/keywords are provided for scanning, but the guidance remains somewhat abstract—there are no concrete examples of what a preference atom looks like, no example output artifact, and no sample input/output to make the process fully executable.

2 / 3

Workflow Clarity

The 8-step workflow is clearly sequenced with logical progression from scoping to inventory to scanning to extraction to confidence rating to clustering to artifact choice to drafting. The confidence framework and artifact choice decision tree serve as validation checkpoints, and the 'contradicted' confidence level explicitly includes a stop condition (ask the user before writing files).

3 / 3

Progressive Disclosure

For a skill of this size (~60 lines) with no need for external references, the content is well-organized into clearly labeled sections (Scope, Workflow, Confidence, Artifact Choice, Output) that are easy to navigate. No bundle files are needed and the structure is appropriately flat.

3 / 3

Total

11

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a well-crafted skill description that clearly articulates a specific, niche capability with explicit trigger guidance. It uses third person voice, lists concrete actions, and provides a comprehensive 'Use when' clause with multiple natural trigger terms. The description is concise yet thorough, making it easy for Claude to distinguish this skill from others.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Extract durable working preferences from recent Cursor chats' and 'convert them into skills, rules, or workflow docs.' These are clear, actionable capabilities.

3 / 3

Completeness

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

3 / 3

Trigger Term Quality

Includes strong natural trigger terms: 'learn preferences', 'mine feedback', 'personalize workflows', 'generate team/person-specific agent guidance', 'Cursor chats'. These cover a good range of terms a user would naturally say.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche: extracting preferences specifically from Cursor chats and converting them into agent guidance artifacts. The combination of 'Cursor chats', 'working preferences', and 'skills/rules/workflow docs' creates a clear, unique identity unlikely to conflict with other skills.

3 / 3

Total

12

/

12

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
cursor/plugins
Reviewed

Table of Contents

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.