Multi-topic batch. The big-ticket item is the skills audit; the rest are smaller patches that compounded during the audit work. ## Skills audit (rules→recipes split) Vendored all 26 skills from /home/samkintop/opt/skills/ into data/skills/ (the boocode-repo-local skill library — see docker-compose change below). Audited via 5 parallel Claude Code agent-teams running the mgechev/skills-best-practices 4-step protocol (Discovery → Logic → Edge Case → self-Architecture-Refinement) per skill, ~2 min wall-clock vs the ~3.7-hour serial estimate. Result: 14 skills surviving (renamed to gerund form, frontmatter matched), 11 deleted (duplicates, BooCode-irrelevant patterns, Claude-already-does- natively), 1 migrated to BOOCHAT.md/BOOCODER.md as an always-true rule (verification-before-completion). Each surviving skill had its description refined to fix specific trigger gaps surfaced by the protocol — 4 real-bug findings landed (dead refs, stale tags, broken sub-file references in the original vendored content). Audit decisions documented in openspec/changes/v1.13.12-skills-audit/ audit-notes.md. Convention codified in BOOCHAT.md/BOOCODER.md "rules vs recipes" sections — future workflow rules go to those files (100% present), recipes stay in data/skills/ (~6% invoke rate in multi-turn per the Codeminer42 measurement). ## Token tracking + stale-stream banner fix (same root cause) ws-frames.ts IsoTimestamp was z.string().min(1) but postgres returns timestamp columns as JS Date objects. Every message_complete / session_updated / chat_updated frame was failing the v1.13.11 Zod gate and being silently dropped. Symptoms: token tracking blank in the UI (no usage frames landed); the 60s no-token-activity timer tripped the stale-stream banner because the frontend's local message state never saw status='streaming' flip to 'complete'. Fix: z.preprocess(v => v instanceof Date ? v.toISOString() : v, z.string().min(1)) applied to the IsoTimestamp primitive. Centralized, no publisher changes, works identically server + web (the parity test still passes). ## Codecontext .codecontextignore auto-install services/codecontext_client.ts now copies the codecontext/.codecontextignore.template into any project's root on the first call to that project if no .codecontextignore exists. One file written per project, idempotent (in-memory Set guard + access-check), silent fallback on read-only project. Stops the upstream empty-source- file parser crash on foreign projects' node_modules — previously required manually copying the template per project. ## Tool-call budget cap 30 → 50 services/inference/budget.ts: BUDGET_READ_ONLY and BUDGET_NO_AGENT bumped to 50 (from 30). BUDGET_NON_READ_ONLY stays at 10 (no write tools landed yet). Real recon sessions were hitting 30 with ~3 turns wasted on codecontext parse failures; legitimate need was ~27, and Architect-class system overviews want deeper recon. Headroom of 20 absorbs failure-retry turns without changing the safety floor — the doom-loop guard (3 identical calls → abort) catches the actual failure mode this cap was guarding against. v1.14 (Phase C outer agent loop) will supersede this via per-agent agent.steps. Throwaway-ish patch but unblocks deeper recon today. ## UI cleanups - ChatPane queued-message dropdown removed. Each queued message now has three buttons: edit (pop back into ChatInput via sendToChat event), force-send (was the dropdown's only useful action), and cancel. Default behavior (send when streaming completes) needs no UI — it's the implicit do-nothing path. - ChatThroughput removed from desktop tab strip (ChatTabBar.tsx). Mobile tab switcher still shows it. ## Plumbing - .gitignore: data/* + !data/AGENTS.md + !data/skills/ negation patterns so the vendored skill library + agent registry become git-tracked while session DB state stays out. - docker-compose.yml: removed /opt/skills:/data/skills override mount. Skills now live in the boocode repo at data/skills/, auditable per-batch. The host-level /opt/skills/ is preserved untouched for any other tools that read from it. - .codecontextignore at repo root: auto-installed when codecontext was first called against /opt/boocode itself; matches the template. - CLAUDE.md: updated to document the v1.13.11 publishFrame wrapper + message_parts table + tool_cost_stats view + DB-integration test pattern + host-side smoke endpoint quirk. (Pre-existing in working tree before this batch; shipped here for completeness.) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Writing Plans
Overview
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
Announce at start: "I'm using the writing-plans skill to create the implementation plan."
Context: If working in an isolated worktree, it should have been created via the superpowers:using-git-worktrees skill at execution time.
Save plans to: docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md
- (User preferences for plan location override this default)
Scope Check
If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.
File Structure
Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.
- Design units with clear boundaries and well-defined interfaces. Each file should have one clear responsibility.
- You reason best about code you can hold in context at once, and your edits are more reliable when files are focused. Prefer smaller, focused files over large ones that do too much.
- Files that change together should live together. Split by responsibility, not by technical layer.
- In existing codebases, follow established patterns. If the codebase uses large files, don't unilaterally restructure - but if a file you're modifying has grown unwieldy, including a split in the plan is reasonable.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
Bite-Sized Task Granularity
Each step is one action (2-5 minutes):
- "Write the failing test" - step
- "Run it to make sure it fails" - step
- "Implement the minimal code to make the test pass" - step
- "Run the tests and make sure they pass" - step
- "Commit" - step
Plan Document Header
Every plan MUST start with this header:
# [Feature Name] Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** [One sentence describing what this builds]
**Architecture:** [2-3 sentences about approach]
**Tech Stack:** [Key technologies/libraries]
---
Task Structure
### Task N: [Component Name]
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
- [ ] **Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
- [ ] **Step 2: Run test to verify it fails**
Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"
- [ ] **Step 3: Write minimal implementation**
```python
def function(input):
return expected
```
- [ ] **Step 4: Run test to verify it passes**
Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS
- [ ] **Step 5: Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
No Placeholders
Every step must contain the actual content an engineer needs. These are plan failures — never write them:
- "TBD", "TODO", "implement later", "fill in details"
- "Add appropriate error handling" / "add validation" / "handle edge cases"
- "Write tests for the above" (without actual test code)
- "Similar to Task N" (repeat the code — the engineer may be reading tasks out of order)
- Steps that describe what to do without showing how (code blocks required for code steps)
- References to types, functions, or methods not defined in any task
Remember
- Exact file paths always
- Complete code in every step — if a step changes code, show the code
- Exact commands with expected output
- DRY, YAGNI, TDD, frequent commits
Self-Review
After writing the complete plan, look at the spec with fresh eyes and check the plan against it. This is a checklist you run yourself — not a subagent dispatch.
1. Spec coverage: Skim each section/requirement in the spec. Can you point to a task that implements it? List any gaps.
2. Placeholder scan: Search your plan for red flags — any of the patterns from the "No Placeholders" section above. Fix them.
3. Type consistency: Do the types, method signatures, and property names you used in later tasks match what you defined in earlier tasks? A function called clearLayers() in Task 3 but clearFullLayers() in Task 7 is a bug.
If you find issues, fix them inline. No need to re-review — just fix and move on. If you find a spec requirement with no task, add the task.
Execution Handoff
After saving the plan, offer execution choice:
"Plan complete and saved to docs/superpowers/plans/<filename>.md. Two execution options:
1. Subagent-Driven (recommended) - I dispatch a fresh subagent per task, review between tasks, fast iteration
2. Inline Execution - Execute tasks in this session using executing-plans, batch execution with checkpoints
Which approach?"
If Subagent-Driven chosen:
- REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development
- Fresh subagent per task + two-stage review
If Inline Execution chosen:
- REQUIRED SUB-SKILL: Use superpowers:executing-plans
- Batch execution with checkpoints for review