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
92%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Critical
Do not install without reviewing
Quality
Discovery
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 clear 'Use when' clause with natural trigger terms. The description is concise yet comprehensive, making it easy for Claude to distinguish this skill from others.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Extract durable working preferences from recent Cursor chats', '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 how users would naturally phrase such requests. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche: extracting preferences from Cursor chats specifically to generate agent guidance documents. The combination of 'Cursor chats', 'working preferences', and 'skills/rules/workflow docs' output makes this unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
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 weakness is the lack of concrete examples—a sample preference atom, a sample output synthesis, or a sample artifact draft would significantly improve actionability. The confidence taxonomy and artifact choice framework are strong differentiators.
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 showing how parent conversation citations, preference profiles, and proposed artifacts should appear.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. Every section serves a purpose—scope, workflow steps, confidence taxonomy, artifact choice, and output format. No unnecessary explanations of concepts Claude already knows. No padding or filler. | 3 / 3 |
Actionability | The workflow steps are clearly enumerated and specific (e.g., scan for markers like 'I prefer', 'always', 'never'), and the preference atom structure is well-defined. However, there are no concrete examples of what a preference atom looks like, what a final output artifact looks like, or how to format the synthesis. The guidance is structured but not copy-paste ready. | 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 levels serve as validation checkpoints (especially 'contradicted' triggering a user check before writing), and the artifact choice step acts as a decision gate. | 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 monolithic walls of text, and the structure supports quick scanning. | 3 / 3 |
Total | 11 / 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- cursor/plugins
- Commit
b8f2564
- Reviewed
Table of Contents
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