LLM Skills
~/catalog/note taking//learn-eval
Note takingGitHub source

Extract & evaluate reusable patterns

/learn-eval

Extract reusable templates from the session, evaluate their quality yourself before saving them, and determine where to save them

affaan-maffaan-m
240.5k
May 20, 2026
MIT License
// skill content

--- description: "Extract reusable patterns from the session, self-evaluate quality before saving, and determine the right save location (Global vs Project)." --- # /learn-eval - Extract, Evaluate, then Save Extends /learn with a quality gate, save-location decision, and knowledge-placement awareness before writing any skill file. ## What to Extract Look for: 1. Error Resolution Patterns : root cause + fix + reusability 2. Debugging Techniques : non-obvious steps, tool combinations 3. Workarounds : library quirks, API limitations, version-specific fixes 4. Project-Specific Patterns : conventions, architecture decisions, integration patterns ## Process 1. Review the session for extractable patterns 2. Identify the most valuable/reusable insight 3. Determine save location: - Ask: "Would this pattern be useful in a different project?" - Global (~/.claude/skills/learned/): Generic patterns usable across 2+ projects (bash compatibility, LLM API behavior, debugging techniques, etc.) - Project (.claude/skills/learned/ in current project): Project-specific knowledge (quirks of a particular config file, project-specific architecture decisions, etc.) - When in doubt, choose Global (moving Global → Project is easier than the reverse) 4. Draft the skill file using this format: ``markdown --- name: pattern-name description: "Under 130 characters" user-invocable: false origin: auto-extracted --- # [Descriptive Pattern Name] **Extracted:** [Date] **Context:** [Brief description of when this applies] ## Problem [What problem this solves - be specific] ## Solution [The pattern/technique/workaround - with code examples] ## When to Use [Trigger conditions] ` 5. **Quality gate : Checklist + Holistic verdict** ### 5a. Required checklist (verify by actually reading files) Execute **all** of the following before evaluating the draft: - [ ] Grep ~/.claude/skills/ and relevant project .claude/skills/ files by keyword to check for content overlap - [ ] Check MEMORY.md (both project and global) for overlap - [ ] Consider whether appending to an existing skill would suffice - [ ] Confirm this is a reusable pattern, not a one-off fix ### 5b. Holistic verdict Synthesize the checklist results and draft quality, then choose **one** of the following: | Verdict | Meaning | Next Action | |---------|---------|-------------| | **Save** | Unique, specific, well-scoped | Proceed to Step 6 | | **Improve then Save** | Valuable but needs refinement | List improvements → revise → re-evaluate (once) | | **Absorb into [X]** | Should be appended to an existing skill | Show target skill and additions → Step 6 | | **Drop** | Trivial, redundant, or too abstract | Explain reasoning and stop | **Guideline dimensions** (informing the verdict, not scored): - **Specificity & Actionability**: Contains code examples or commands that are immediately usable - **Scope Fit**: Name, trigger conditions, and content are aligned and focused on a single pattern - **Uniqueness**: Provides value not covered by existing skills (informed by checklist results) - **Reusability**: Realistic trigger scenarios exist in future sessions 6. **Verdict-specific confirmation flow** - **Improve then Save**: Present the required improvements + revised draft + updated checklist/verdict after one re-evaluation; if the revised verdict is **Save**, save after user confirmation, otherwise follow the new verdict - **Save**: Present save path + checklist results + 1-line verdict rationale + full draft → save after user confirmation - **Absorb into [X]**: Present target path + additions (diff format) + checklist results + verdict rationale → append after user confirmation - **Drop**: Show checklist results + reasoning only (no confirmation needed) 7. Save / Absorb to the determined location ## Output Format for Step 5 ` ### Checklist - [x] skills/ grep: no overlap (or: overlap found → details) - [x] MEMORY.md: no overlap (or: overlap found → details) - [x] Existing skill append: new file appropriate (or: should append to [X]) - [x] Reusability: confirmed (or: one-off → Drop) ### Verdict: Save / Improve then Save / Absorb into [X] / Drop **Rationale:** (1-2 sentences explaining the verdict) `` ## Design Rationale This version replaces the previous 5-dimension numeric scoring rubric (Specificity, Actionability, Scope Fit, Non-redundancy, Coverage scored 1-5) with a checklist-based holistic verdict system. Modern frontier models (Opus 4.6+) have strong contextual judgment : forcing rich qualitative signals into numeric scores loses nuance and can produce misleading totals. The holistic approach lets the model weigh all factors naturally, producing more accurate save/drop decisions while the explicit checklist ensures no critical check is skipped. ## Notes - Don't extract trivial fixes (typos, simple syntax errors) - Don't extract one-time issues (specific API outages,

// original public source
affaan-m/ECC
/commands/learn-eval.md
License: MIT License
Independent project, not affiliated with Anthropic. This skill remains the property of its original author.
// install this skill
Paste this command in your terminal at the root of your project:
mkdir -p .claude/commands && curl -o ".claude/commands/learn-eval.md" "https://raw.githubusercontent.com/affaan-m/ECC/main/commands/learn-eval.md"
Then in Claude Code, type /learn-eval to activate it.
open_in_newOpen original source
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// information
Creatoraffaan-m
Stars 240.5k
CategoryNote taking
LicenseMIT License
UpdatedMay 20, 2026
Format.md
AccessFree
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