Claude Code's (and Copilot's) native plugin installer has zero awareness of .apm/ nesting -- it convention-scans only flat skills/, agents/, commands/, hooks.json at each plugin's root. Confirmed via strings on the installed claude binary and live installs of git@holocron/gitea@holocron/kyberforge@ holocron, all reporting Skills(0) Agents(0) Hooks(0) post ADR-0015's apm conversion. Root cause (apm_cli/core/plugin_manifest.py): apm's plugin.json compiler deliberately strips skills/agents/commands keys, assuming the host already auto-discovers those convention directories -- it has no model of .apm/ being host-visible at all. Separately, apm's own bundle exporter (apm_cli/bundle/plugin_exporter.py, behind `apm pack --format plugin`) implements the correct .apm/ -> flat mapping, but only ever targeted build/<name>-<version>/, a path nothing in marketplace.json's source: points at. scripts/sync-plugin-content.sh wraps that bundle exporter and copies its agents/, skills/, commands/, instructions/, extensions/, and merged hooks.json back into each plugin's own root as a second tracked compiled-output category -- same governance status as .claude-plugin/plugin.json: generated from .apm/, never hand-edited. tests/ subdirectories are excluded from the mirror (dev fixtures, not host-visible runtime content; several hardcode a relative repo-root walk-up sized for the .apm/-nested depth, which breaks when duplicated one level shallower). Applied for real across all 6 plugins and verified two ways: `claude plugin validate --strict` passes on every real plugin directory, and a live `claude --plugin-dir <path> -p "list skills/agents"` behavioral test confirms content is now actually discovered. Also, from the same issue #90 review round: - scripts/check-manifests.sh pointed at each plugin's root-level plugin.json (checking skills/hooks/mcpServers/agents pointer fields) -- that file was a stale near-duplicate of .claude-plugin/plugin.json nothing else read or wrote, now deleted across all 6 plugins. check-manifests.sh is rewritten to validate .claude-plugin/plugin.json instead, and drops the pointer-field checks entirely (nothing to check -- those fields are correctly absent by design). Content-presence drift is now check-plugin-content-sync's job, a new pre-push hook wired in .pre-commit-config.yaml. docs/adr/0017 records the root cause and decision in full, including two rejected alternatives (patching plugin.json's path fields directly -- apm's compiler strips them on every run; pointing marketplace.json at apm pack's build/ output -- a version-suffixed non-source directory nothing can install from without an extra build step). ADR-0015 and CONTEXT.md are updated to point at it. Refs: #90
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name, description
| name | description |
|---|---|
| tdd | Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development. |
Test-Driven Development
Philosophy
Core principle: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't.
Good tests are integration-style: they exercise real code paths through public APIs. They describe what the system does, not how it does it. A good test reads like a specification - "user can checkout with valid cart" tells you exactly what capability exists. These tests survive refactors because they don't care about internal structure.
Bad tests are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.
See tests.md for examples and mocking.md for mocking guidelines.
Anti-Pattern: Horizontal Slices
DO NOT write all tests first, then all implementation. This is "horizontal slicing" - treating RED as "write all tests" and GREEN as "write all code."
This produces crap tests:
- Tests written in bulk test imagined behavior, not actual behavior
- You end up testing the shape of things (data structures, function signatures) rather than user-facing behavior
- Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine
- You outrun your headlights, committing to test structure before understanding the implementation
Correct approach: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it.
WRONG (horizontal):
RED: test1, test2, test3, test4, test5
GREEN: impl1, impl2, impl3, impl4, impl5
RIGHT (vertical):
RED→GREEN: test1→impl1
RED→GREEN: test2→impl2
RED→GREEN: test3→impl3
...
Workflow
1. Planning
When exploring the codebase, use the project's domain glossary so that test names and interface vocabulary match the project's language, and respect ADRs in the area you're touching.
Before writing any code:
- Confirm with user what interface changes are needed
- Confirm with user which behaviors to test (prioritize)
- Identify opportunities for deep modules (small interface, deep implementation)
- Design interfaces for testability
- List the behaviors to test (not implementation steps)
- Get user approval on the plan
Ask: "What should the public interface look like? Which behaviors are most important to test?"
You can't test everything. Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.
2. Tracer Bullet
Write ONE test that confirms ONE thing about the system:
RED: Write test for first behavior → test fails
GREEN: Write minimal code to pass → test passes
This is your tracer bullet - proves the path works end-to-end.
3. Incremental Loop
For each remaining behavior:
RED: Write next test → fails
GREEN: Minimal code to pass → passes
Rules:
- One test at a time
- Only enough code to pass current test
- Don't anticipate future tests
- Keep tests focused on observable behavior
4. Refactor
After all tests pass, look for refactor candidates:
- Extract duplication
- Deepen modules (move complexity behind simple interfaces)
- Apply SOLID principles where natural
- Consider what new code reveals about existing code
- Run tests after each refactor step
Never refactor while RED. Get to GREEN first.
Checklist Per Cycle
[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Code is minimal for this test
[ ] No speculative features added