Project Learnings

Capture project-specific patterns and anti-patterns into the project's agent configuration file. This creates a self-improving feedback loop where discoveries from debugging, development, and review make future sessions smarter.

Important: Only project-specific knowledge qualifies. Generic programming advice does not belong in the project configuration.

Step 1: Evaluate Discovery

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

If NO to all criteria -> STOP. Do not add generic programming knowledge to the project configuration. 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 Configuration

1. Find the project's agent configuration file:

• Check the repository root first for a project-level configuration
• If not found, check if there's a project-level .agents/ directory

1. 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

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

1. 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 configuration file 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's 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 configuration (section name, after which line/entry)
3. Why this qualifies as project-specific

Options:

• "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. Add the entry to the configuration file 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: Captures project-specific patterns, gotchas, and anti-patterns discovered during debugging or development into the project's agent configuration file, creating a self-improving knowledge base. Capabilities needed: File reading (to check existing configuration), file editing (to add entries), user interaction (to confirm additions). Adaptation guidance: This skill writes to a project-level configuration file (the equivalent of CLAUDE.md or a similar project instructions file). Adapt the file path detection in Step 2 to match your platform's convention for storing project-level agent instructions. The core logic of evaluating, formatting, and confirming learnings is platform-agnostic.