v1.13.12: skills audit + token-tracking fix + codecontext + cap50 + UI cleanups

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>
This commit is contained in:
2026-05-22 18:58:30 +00:00
parent bc376c878d
commit 0fa46cd06c
80 changed files with 6950 additions and 39 deletions

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---
name: systematic-debugging
description: Use when encountering any bug, test failure, unexpected behavior, build failure, or compile error, before proposing fixes. Also use when asked to debug, investigate, or diagnose an issue.
---
# Systematic Debugging
## Overview
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
**Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
**Violating the letter of this process is violating the spirit of debugging.**
## The Iron Law
```
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
```
If you haven't completed Phase 1, you cannot propose fixes.
## When to Use
Use for ANY technical issue:
- Test failures
- Bugs in production
- Unexpected behavior
- Performance problems
- Build failures
- Integration issues
**Use this ESPECIALLY when:**
- Under time pressure (emergencies make guessing tempting)
- "Just one quick fix" seems obvious
- You've already tried multiple fixes
- Previous fix didn't work
- You don't fully understand the issue
**Don't skip when:**
- Issue seems simple (simple bugs have root causes too)
- You're in a hurry (rushing guarantees rework)
- Manager wants it fixed NOW (systematic is faster than thrashing)
## The Four Phases
You MUST complete each phase before proceeding to the next.
### Phase 1: Root Cause Investigation
**BEFORE attempting ANY fix:**
1. **Read Error Messages Carefully**
- Don't skip past errors or warnings
- They often contain the exact solution
- Read stack traces completely
- Note line numbers, file paths, error codes
2. **Reproduce Consistently**
- Can you trigger it reliably?
- What are the exact steps?
- Does it happen every time?
- If not reproducible → gather more data, don't guess
3. **Check Recent Changes**
- What changed that could cause this?
- Git diff, recent commits
- New dependencies, config changes
- Environmental differences
4. **Gather Evidence in Multi-Component Systems**
**WHEN system has multiple components (CI → build → signing, API → service → database):**
**BEFORE proposing fixes, add diagnostic instrumentation:**
```
For EACH component boundary:
- Log what data enters component
- Log what data exits component
- Verify environment/config propagation
- Check state at each layer
Run once to gather evidence showing WHERE it breaks
THEN analyze evidence to identify failing component
THEN investigate that specific component
```
**Example (multi-layer system):**
```bash
# Layer 1: Workflow
echo "=== Secrets available in workflow: ==="
echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"
# Layer 2: Build script
echo "=== Env vars in build script: ==="
env | grep IDENTITY || echo "IDENTITY not in environment"
# Layer 3: Signing script
echo "=== Keychain state: ==="
security list-keychains
security find-identity -v
# Layer 4: Actual signing
codesign --sign "$IDENTITY" --verbose=4 "$APP"
```
**This reveals:** Which layer fails (secrets → workflow ✓, workflow → build ✗)
5. **Trace Data Flow**
**WHEN error is deep in call stack:**
See `root-cause-tracing.md` in this directory for the complete backward tracing technique.
**Quick version:**
- Where does bad value originate?
- What called this with bad value?
- Keep tracing up until you find the source
- Fix at source, not at symptom
### Phase 2: Pattern Analysis
**Find the pattern before fixing:**
1. **Find Working Examples**
- Locate similar working code in same codebase
- What works that's similar to what's broken?
2. **Compare Against References**
- If implementing pattern, read reference implementation COMPLETELY
- Don't skim - read every line
- Understand the pattern fully before applying
3. **Identify Differences**
- What's different between working and broken?
- List every difference, however small
- Don't assume "that can't matter"
4. **Understand Dependencies**
- What other components does this need?
- What settings, config, environment?
- What assumptions does it make?
### Phase 3: Hypothesis and Testing
**Scientific method:**
1. **Form Single Hypothesis**
- State clearly: "I think X is the root cause because Y"
- Write it down
- Be specific, not vague
2. **Test Minimally**
- Make the SMALLEST possible change to test hypothesis
- One variable at a time
- Don't fix multiple things at once
3. **Verify Before Continuing**
- Did it work? Yes → Phase 4
- Didn't work? Form NEW hypothesis
- DON'T add more fixes on top
4. **When You Don't Know**
- Say "I don't understand X"
- Don't pretend to know
- Ask for help
- Research more
### Phase 4: Implementation
**Fix the root cause, not the symptom:**
1. **Create Failing Test Case**
- Simplest possible reproduction
- Automated test if possible
- One-off test script if no framework
- MUST have before fixing
- Use the `superpowers:test-driven-development` skill for writing proper failing tests
2. **Implement Single Fix**
- Address the root cause identified
- ONE change at a time
- No "while I'm here" improvements
- No bundled refactoring
3. **Verify Fix**
- Test passes now?
- No other tests broken?
- Issue actually resolved?
4. **If Fix Doesn't Work**
- STOP
- Count: How many fixes have you tried?
- If < 3: Return to Phase 1, re-analyze with new information
- **If ≥ 3: STOP and question the architecture (step 5 below)**
- DON'T attempt Fix #4 without architectural discussion
5. **If 3+ Fixes Failed: Question Architecture**
**Pattern indicating architectural problem:**
- Each fix reveals new shared state/coupling/problem in different place
- Fixes require "massive refactoring" to implement
- Each fix creates new symptoms elsewhere
**STOP and question fundamentals:**
- Is this pattern fundamentally sound?
- Are we "sticking with it through sheer inertia"?
- Should we refactor architecture vs. continue fixing symptoms?
**Discuss with your human partner before attempting more fixes**
This is NOT a failed hypothesis - this is a wrong architecture.
## Red Flags - STOP and Follow Process
If you catch yourself thinking:
- "Quick fix for now, investigate later"
- "Just try changing X and see if it works"
- "Add multiple changes, run tests"
- "Skip the test, I'll manually verify"
- "It's probably X, let me fix that"
- "I don't fully understand but this might work"
- "Pattern says X but I'll adapt it differently"
- "Here are the main problems: [lists fixes without investigation]"
- Proposing solutions before tracing data flow
- **"One more fix attempt" (when already tried 2+)**
- **Each fix reveals new problem in different place**
**ALL of these mean: STOP. Return to Phase 1.**
**If 3+ fixes failed:** Question the architecture (see Phase 4.5)
## your human partner's Signals You're Doing It Wrong
**Watch for these redirections:**
- "Is that not happening?" - You assumed without verifying
- "Will it show us...?" - You should have added evidence gathering
- "Stop guessing" - You're proposing fixes without understanding
- "Ultrathink this" - Question fundamentals, not just symptoms
- "We're stuck?" (frustrated) - Your approach isn't working
**When you see these:** STOP. Return to Phase 1.
## Common Rationalizations
| Excuse | Reality |
|--------|---------|
| "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. |
| "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. |
| "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. |
| "I'll write test after confirming fix works" | Untested fixes don't stick. Test first proves it. |
| "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. |
| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |
| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |
| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |
## Quick Reference
| Phase | Key Activities | Success Criteria |
|-------|---------------|------------------|
| **1. Root Cause** | Read errors, reproduce, check changes, gather evidence | Understand WHAT and WHY |
| **2. Pattern** | Find working examples, compare | Identify differences |
| **3. Hypothesis** | Form theory, test minimally | Confirmed or new hypothesis |
| **4. Implementation** | Create test, fix, verify | Bug resolved, tests pass |
## When Process Reveals "No Root Cause"
If systematic investigation reveals issue is truly environmental, timing-dependent, or external:
1. You've completed the process
2. Document what you investigated
3. Implement appropriate handling (retry, timeout, error message)
4. Add monitoring/logging for future investigation
**But:** 95% of "no root cause" cases are incomplete investigation.
## Supporting Techniques
These techniques are part of systematic debugging and available in this directory:
- **`root-cause-tracing.md`** - Trace bugs backward through call stack to find original trigger
- **`defense-in-depth.md`** - Add validation at multiple layers after finding root cause
- **`condition-based-waiting.md`** - Replace arbitrary timeouts with condition polling
**Related skills:**
- **superpowers:test-driven-development** - For creating failing test case (Phase 4, Step 1)
- **superpowers:verification-before-completion** - Verify fix worked before claiming success
## Real-World Impact
From debugging sessions:
- Systematic approach: 15-30 minutes to fix
- Random fixes approach: 2-3 hours of thrashing
- First-time fix rate: 95% vs 40%
- New bugs introduced: Near zero vs common