# Project Learnings

> Captures project-specific patterns and anti-patterns into the project's configuration. Loaded by other skills (bug-killer, feature-dev, etc.) when they discover project-specific knowledge worth encoding for future sessions.

- Skill: `majiayu000/project-learnings-7` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/project-learnings-7`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/project-learnings-7/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/majiayu000/project-learnings-7

---


# Project Learnings

Capture project-specific patterns and anti-patterns into the project's knowledge base (e.g., CLAUDE.md, .cursorrules, or equivalent). This creates a self-improving feedback loop where discoveries from debugging, development, and review make future sessions smarter.

Only project-specific knowledge qualifies. Generic programming advice does not belong in a project knowledge base.

---

## Step 1: Evaluate Discovery

Determine if the finding qualifies as project-specific. The finding must pass at least ONE of these criteria:

| Criteria | Example That Qualifies | Example That Does Not |
|----------|------------------------|----------------------|
| Would a developer unfamiliar with this project likely hit this issue? | "The `processOrder()` function expects amounts in cents, not dollars" | "Always validate function inputs" |
| Is this pattern specific to this codebase's architecture, APIs, or conventions? | "The `UserProfile` type has an optional `metadata` field that is always present at runtime" | "Use TypeScript strict mode" |
| Is it something not covered by standard documentation? | "Never call `db.query()` without the `timeout` option -- the default is infinite" | "Use async/await instead of callbacks" |

**If NO to all criteria -> STOP.** Do not add generic programming knowledge. Return to the calling skill and report that no project-specific learning was found.

**If YES to any -> proceed to Step 2.**

---

## Step 2: Read Existing Project Knowledge Base

1. **Find the project's knowledge base file:**
   - Check the repository root for CLAUDE.md, .cursorrules, or similar AI instruction files
   - If not found, check if there is a project-level configuration directory

2. **Parse existing content:**
   - Understand the existing structure, headings, and conventions
   - Look for sections where this learning would fit (e.g., "Known Gotchas", "Bug Patterns", "Conventions", "Known Challenges")
   - Check for duplicate or similar entries already present

3. **If a similar entry already exists -> STOP.** Report to the calling skill that this knowledge is already captured. Do not create duplicates.

4. **Identify placement:**
   - If an appropriate section exists, plan to add the entry there
   - If no appropriate section exists, plan to propose a new section (e.g., `## Known Gotchas` or `## Project-Specific Patterns`)
   - New sections should be placed after the main documentation sections but before appendices or settings

---

## Step 3: Format the Learning

Write a concise, actionable instruction following these rules:

**Format:**
- Use imperative form: "Always validate X before calling Y"
- Include the WHY: "...because the API returns dates as strings, not Date objects"
- Keep it to 1-3 lines
- Follow the existing knowledge base style and conventions

**Templates:**

For bug patterns:
```
- **[Area/Component]**: [What to do/avoid] -- [why, with specific details]
```

For API gotchas:
```
- `functionName()` in `path/to/file`: [What is surprising about it] -- [consequence if ignored]
```

For architectural constraints:
```
- [Constraint description] -- [why it exists and what breaks if violated]
```

**Examples of well-formatted learnings:**
- **Order processing**: Always multiply amounts by 100 before passing to `processOrder()` -- it expects cents, not dollars
- `db.query()` in `src/database.ts`: Always pass the `timeout` option -- the default is infinite and has caused production hangs (30 second timeout recommended)
- Never import from `internal/` directories in `src/api/` -- the build system treats these as separate compilation units and circular dependencies will silently break HMR

---

## Step 4: Confirm with User

Present the proposed addition to the user.

Show:
1. The exact text to be added
2. Where it will be placed in the knowledge base (section name, after which line/entry)
3. Why this qualifies as project-specific

Prompt the user:
- **"Add this"** -- Write the entry as proposed
- **"Edit before adding"** -- User provides modified text, then write that instead
- **"Skip"** -- Do not add anything, return to calling skill

---

## Step 5: Write Update

If the user confirmed (or provided edited text):

1. Edit the knowledge base file to add the entry at the identified location
2. If a new section was needed, create the section heading first
3. Verify the edit was applied correctly by reading the modified area
4. Report success to the calling skill with a summary of what was added

If the user chose "Skip":
- Report to the calling skill that the learning was declined
- Do not modify any files

---

## Integration Notes

**What this component does:** Evaluates debugging and development discoveries for project-specific relevance, then captures qualifying learnings into the project's AI knowledge base file (CLAUDE.md or equivalent) with user approval.

**Capabilities needed:**
- File read/edit operations (to read and update the project knowledge base)
- User interaction (to confirm additions)
- Search for files matching patterns (to locate the knowledge base file)

**Adaptation guidance:**
- The target file (CLAUDE.md) is specific to Claude Code -- adapt the file detection logic in Step 2 to find your platform's equivalent (e.g., .cursorrules for Cursor, .github/copilot-instructions.md for Copilot)
- The evaluation criteria in Step 1 are universal -- keep them regardless of platform
- This skill is always invoked by other skills (bug-killer, feature-dev), never directly by the user

**Configurable parameters:** None