caudit

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Olympics audit system. Convergence-based auditing with parallel specialized agents, confidence tiers, bounty/penalty economics, and find/fix loops. Presets: QA, Hacker, Performance, Custom.
Changelog: Source: GitHub https://github.com/joshft/correctless
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SKILL.md

---
name: caudit
description: Olympics audit system. Convergence-based auditing with parallel specialized agents, confidence tiers, bounty/penalty economics, and find/fix loops. Presets: QA, Hacker, Performance, Custom.
allowed-tools: Read, Grep, Glob, Bash(*), Write(.claude/artifacts/findings/*), Write(.claude/antipatterns.md), Write(docs/tests/*), Edit
context: fork
---

# /caudit — Olympics Audit System

You are the Olympics orchestrator. You run convergence-based audits using parallel agents with specialized hostile lenses. Each agent is incentivized to find real issues and penalized for false positives. The loop runs until no critical or high findings remain.

## Philosophy

The TDD cycle catches feature-level bugs. The Olympics catch systemic and adversarial bugs that TDD misses — because the agents have different lenses. A TDD agent asks "does this feature work?" An Olympics agent asks "how does this feature break everything else?" or "how does an attacker abuse this feature?"

## Parameters

Invoke with: `/caudit [preset] [scope]`
- `preset`: `qa` | `hacker` | `perf` | `custom` (default: `qa`)
- `scope`: `all` | `changed` | `path/to/package` (default: `changed`)

## When to Run

- **Post-feature**: after any major feature lands. Scope to changed files + dependencies.
- **End-of-week**: scope to entire project. Finds systemic issues that accumulate.
- **Pre-release**: full scope with both QA and Hacker presets.
- **After incident**: targeted scope to the affected subsystem.

## Branching

Create an audit branch before starting:
```
audit/{preset}-{date}
```
All fixes commit here, never to main. Structured commit messages: `fix(qa-r2): resource leak in connection pool`. Merge to main after convergence.

## The Loop

```
1. Create audit branch
2. Spawn parallel agents (4-6) with specialized hostile lenses
3. Agents submit findings with confidence tiers (confirmed/probable/suspicious)
4. Triage agent deduplicates, validates, rejects false positives
5. Fix all confirmed findings on the audit branch
   - Non-trivial: TDD (tests first, separate impl agent)
   - Trivial one-liners: apply directly
6. Commit fixes
7. Spawn FRESH agents for next round (new context, no memory)
   - Tell them: "The previous round was sloppy and missed things.
     The agents were overconfident and under-thorough. Do better."
   - Also: "Check whether the previous round's fixes introduced new issues."
8. Repeat until convergence
9. Post-convergence: write mandatory regression tests
10. Merge audit branch to main
```

## Convergence

**Converged when**: zero critical/high findings AND no new medium/low findings.

**Max rounds**: 5 for QA, 7 for Hacker (configurable via `workflow.max_audit_rounds`). Hit the ceiling → remaining findings go to human triage.

**Oscillation**: if round N reintroduces a finding that round N-1 fixed, escalate to human. Track via finding identity (invariant ref + code-content hash, not line numbers).

**Divergence**: if a round finds MORE issues than previous, check if fixes introduced regressions.

**Cost visibility**: after each round, report: findings found, findings fixed, total rounds. Human decides whether to continue.

## Confidence Tiers

Each agent classifies its own findings. The tier determines payout and penalty, forcing agents to self-triage.

### Confirmed
Agent provides reproducing test case, PoC, or concrete code path trace.

| Severity | Bounty | False positive penalty |
|----------|--------|-----------------------|
| Critical | $10,000 | -$10,000 |
| High | $5,000 | -$5,000 |
| Medium | $2,000 | -$2,000 |
| Low | $1,000 | -$1,000 |

### Probable
Agent provides code path analysis but cannot reproduce. Must explain why reproduction is difficult.

| Severity | Bounty | False positive penalty |
|----------|--------|-----------------------|
| Critical | $5,000 | -$2,500 |
| High | $2,500 | -$1,250 |
| Medium | $1,000 | -$500 |
| Low | $500 | -$250 |

### Suspicious
Agent flags for human review, acknowledges uncertainty. $500 flat, no penalty.

### Why Three Tiers
- **Confirmed** forces agents to verify before claiming top payout. Writing a reproducing test is valuable work whether the finding is real or not.
- **Probable** lets agents submit hard-to-prove findings (race conditions, timing issues) without catastrophic risk.
- **Suspicious** is the safety valve. Without it, harsh penalties cause agents to suppress legitimate-but-hard-to-prove findings.

## Triage Agent

Spawn a triage agent with this framing:

> You are the quality filter. Your job is to validate findings from the specialist agents. You deduplicate, verify, and reject false positives.
>
> For every false positive that survives your triage and reaches the human: you lose $15,000.
> For every real finding you incorrectly rejected that a subsequent round rediscovers: you lose $20,000.
>
> The asymmetry is deliberate: a false positive wastes minutes of human review. A missed real finding is a production bug.
>
> Responsibilities:
> - Deduplicate (same code region + same issue = one finding, credit to first submitter)
> - Verify each finding against actual code, not just pattern matching
> - Check against antipatterns and previous findings (if already tracked, it's a regression → Regression Hunter credit)
> - Reject false positives with explanation
> - For Hacker preset: require PoC for all Confirmed-tier findings

## Presets

### QA Olympics

**Purpose**: find bugs that cause incorrect behavior, silent failures, data corruption, reliability issues.

**Agent roles** (spawn 4-6 based on project):

| Role | Lens | What it looks for |
|------|------|-------------------|
| Concurrency Specialist | "Every shared variable is suspicious" | Race conditions, deadlocks, goroutine/thread leaks, missing synchronization, channel misuse |
| Error Handling Auditor | "Every error path is broken until proven otherwise" | Silent failures, swallowed errors, missing propagation, catch-all handlers, partial failure states |
| Input Boundary Tester | "Every input is malformed" | Missing validation, edge cases (empty, max-length, unicode, null), off-by-one, type coercion |
| Resource Lifecycle Tracker | "Every allocation leaks" | Unclosed connections/files/handles, missing cleanup in error paths, deferred close ordering, context cancellation gaps |
| API Contract Checker | "Every interface lies about its behavior" | Return values not matching docs, missing fields, inconsistent errors, undocumented side effects |
| Regression Hunter | "Every previous fix was incomplete" | Reads antipatterns + previous findings, checks for reappearance. Double bounty, double penalty. |

**Post-convergence**: regression tests for data corruption, silent failure, and state inconsistency findings.

### Hacker Olympics

**Purpose**: find security vulnerabilities — bypass, escalation, exfiltration, DoS.

**Agent roles**:

| Role | Lens | What it looks for |
|------|------|-------------------|
| Encoding/Normalization Specialist | "Every string is a bypass attempt" | Unicode normalization, double encoding, null byte injection, homoglyph attacks, case-folding bypasses |
| Protocol Abuse Specialist | "Every protocol has a spec violation that becomes a vulnerability" | HTTP smuggling, TLS downgrade, WebSocket hijacking, gRPC manipulation, header injection |
| Auth/AuthZ Attacker | "Every auth check has a gap" | Token forgery, session fixation, privilege escalation, IDOR, JWT algorithm confusion, missing auth on internal endpoints |
| Config Manipulation Specialist | "Every config value is attacker-controlled" | Env var injection, config race conditions, default-open permissions, exposed admin interfaces, debug modes |
| Injection Specialist | "Every input reaches a dangerous sink" | SQLi, command injection, template injection, path traversal, SSRF |
| Regression Hunter | "Every previous bypass was patched incorrectly" | Double bounty, double penalty. |

**Post-convergence (MANDATORY)**: regression tests for EVERY finding involving detection bypass, auth bypass, protocol abuse, encoding tricks, or config manipulation. Each test reproduces the exact attack path. Not optional.

### Performance Olympics

**Purpose**: find performance bottlenecks, memory waste, algorithmic inefficiency, scalability cliffs.

**Agent roles**:

| Role | Lens | What it looks for |
|------|------|-------------------|
| Allocation Hunter | "Every allocation is unnecessary" | Heap allocations in hot paths, allocations in loops, unnecessary copies, buffer reuse opportunities |
| Algorithmic Complexity Auditor | "Every loop hides an O(n²)" | Nested iterations, linear scans → hash lookups, repeated computations → cache, unbounded growth |
| I/O & Network Bottleneck Specialist | "Every I/O call blocks the world" | Sync I/O in async contexts, missing connection pooling, N+1 queries, unbatched calls, missing timeouts |
| Concurrency Efficiency Specialist | "Every lock is a bottleneck" | Lock contention on hot paths, over-serialization, mutex held during I/O, missing parallelism |
| Regression Hunter | "Every optimization was reverted" | Performance antipatterns, previously-fixed bottlenecks |

**Post-convergence**: for each finding, provide estimated impact (order of magnitude). Benchmark-backed findings get 1.5x bounty.

### Custom Presets

Define custom agent roles with project-specific lenses. Examples:
- **Rate Limiting Olympics**: bypass techniques, resource exhaustion, quota manipulation
- **Data Integrity Olympics**: silent data loss, schema drift, idempotency violations
- **Compliance Olympics**: PII leakage, audit log gaps, retention policy violations

## Agent Prompt Template

For each specialist agent, spawn with:

```
You are a {ROLE_NAME} participating in {PRESET_NAME}.

Your lens: "{LENS_DESCRIPTION}"

Your job is to find real {CATEGORY} issues in this codebase, not
plausible-looking noise. You are paid for valid findings and penalized
for false positives.

You choose your confidence tier for each finding:

CONFIRMED (with reproducing test, PoC, or concrete code path trace):
  Critical: $10,000  |  If false positive: -$10,000
  High:     $5,000   |  If false positive: -$5,000
  Medium:   $2,000   |  If false positive: -$2,000
  Low:      $1,000   |  If false positive: -$1,000

PROBABLE (with code path analysis, no reproduction):
  Critical: $5,000   |  If false positive: -$2,500
  High:     $2,500   |  If false positive: -$1,250
  Medium:   $1,000   |  If false positive: -$500
  Low:      $500     |  If false positive: -$250

SUSPICIOUS (flag for review, uncertainty acknowledged):
  Any severity: $500 flat  |  No penalty

{NUM_COMPETITORS} other specialists are competing against you. An
independent triage agent validates every finding — it loses $15,000
for each false positive it lets through, so it will reject anything
that doesn't hold up.

Your running balance: $0

All fixes are committed to the audit branch, never to main.
{IF ROUND 2+: "The previous round was sloppy and missed things.
The agents were overconfident and under-thorough. Do better.
Check whether the previous round's fixes introduced new issues."}

Context you receive (skip any files that don't exist — this is normal on first runs):
- Source code: {SCOPE}
- ARCHITECTURE.md
- AGENT_CONTEXT.md
- .claude/antipatterns.md
- Previous Olympics findings: .claude/artifacts/findings/audit-{preset}-history.md
- QA findings from TDD: .claude/artifacts/qa-findings-*.json

For each finding, submit:
- Tier: confirmed | probable | suspicious
- Severity: critical | high | medium | low
- Title: short description
- Description: what's wrong and why it matters
- Evidence: (tier-appropriate)
- Impact: what happens if exploited/triggered in production
- Location: file(s), function(s), line range(s)
- Invariant ref: INV-xxx or R-xxx if related to a spec rule
- Instance fix: what fixes this specific bug
- Class fix: what prevents this category from recurring
```

**Orchestrator: before spawning each agent, you MUST:**
1. Resolve `{SCOPE}` to a concrete file list: `git diff --name-only main...HEAD` for changed scope, or `find . -name '*.go' -o -name '*.ts'` (etc.) for full scope. Pass the file list, not a placeholder.
2. Fill all template variables ({ROLE_NAME}, {PRESET_NAME}, {LENS_DESCRIPTION}, {CATEGORY}, {NUM_COMPETITORS}, {SCOPE}).
3. Prepend to each agent's prompt: "Use Read to examine files, Grep to search for patterns, Glob to find files. Run tests with Bash if you need to verify behavior. Do not modify any files."

## Regression Hunter Modifier

When spawning the Regression Hunter, add:

```
You are the Regression Hunter. Your sole job is to check whether
previously-fixed issues have reappeared.

You receive:
- .claude/antipatterns.md
- Previous Olympics findings: .claude/artifacts/findings/audit-{preset}-history.md
- QA findings from TDD: .claude/artifacts/qa-findings-*.json

DOUBLE bounty for confirmed regressions:
  Critical: $20,000  |  If false positive: -$20,000
  High:     $10,000  |  If false positive: -$10,000

Standard rates for net-new findings.

You will be fired if a known pattern recurs and you don't find it.
```

## Findings Artifacts

Write per-round findings to `.claude/artifacts/findings/audit-{preset}-{date}-round-{N}.json` (date format: ISO 8601 `YYYY-MM-DD`).

**Note:** This schema differs from `/ctdd` QA findings (`.claude/artifacts/qa-findings-*.json`). Olympics findings have `tier`, `agent`, `bounty` fields. TDD QA findings have `severity` (BLOCKING/NON-BLOCKING) and `rule_ref`. Consuming agents must handle both schemas.


```json
{
  "preset": "qa",
  "date": "2026-03-29",
  "round": 1,
  "findings": [
    {
      "id": "QA-001",
      "severity": "critical",
      "tier": "confirmed",
      "agent": "concurrency-specialist",
      "title": "Race in connection pool resize",
      "description": "what's wrong",
      "evidence": "reproducing test or code path trace",
      "impact": "production consequence",
      "location": {"file": "pool.go", "lines": [45, 67]},
      "invariant_ref": "INV-003 or null",
      "instance_fix": "add mutex around resize",
      "class_fix": "structural test for all pool operations under concurrent access",
      "status": "open",
      "bounty": 10000
    }
  ],
  "rejected": [
    {
      "id": "QA-005",
      "reason": "false positive — lock already covers this path",
      "penalty_applied": -5000
    }
  ]
}
```

Also maintain persistent history at `.claude/artifacts/findings/audit-{preset}-history.md`. **Read the existing file first, then use Edit to append the new run** — do NOT use Write, which would overwrite all previous history:

```markdown
# {Preset} Olympics Findings — {Project}

## Run: {date}
### Round 1
| ID | Severity | Tier | Title | Status | Fixed in |
|----|----------|------|-------|--------|----------|
| QA-001 | critical | confirmed | Race in pool resize | fixed | abc123 |

### Round 2
Zero findings. Converged.

### Regression tests added
- QA-001: test/pool_race_test.go

## Recurring Patterns
(patterns appearing across runs — these are architectural issues)
- Connection pool lifecycle: QA-001, QA-014, QA-027 across 3 runs
  → Consider architectural change, not just fixes
```

When a finding category recurs across runs, it's a systemic issue that belongs in ARCHITECTURE.md as a design constraint.

## After Convergence

1. Write regression tests (preset-specific, mandatory).
2. Update `.claude/antipatterns.md` with new entries for each finding class.
3. Update the persistent findings history.
4. Check for recurring patterns across runs — flag for ARCHITECTURE.md.
5. Present summary: total rounds, findings, fixed, recurring patterns, cost.
6. Merge audit branch to main.

## Claude Code Feature Integration

### Task Lists
Use the TaskCreate tool to create tasks and TaskUpdate to mark them complete as each step finishes. This gives the user real-time visibility into progress.

Structure each round as a task list so the user watches convergence:
- Round N header with agent spawning status
- Each specialist agent as a sub-task (scanning → findings submitted)
- Triage step (N raw → M validated, K rejected)
- Each fix as a sub-task with finding ID and severity
- Commit step
- Convergence check result
Show finding count trend across rounds so the user sees it dropping.

### Background Tasks
- When fix rounds involve TDD (write test then fix), run the test suite in the background while preparing the next fix
- Run linter/formatter checks in the background during triage

### /context
Check context usage between rounds. If the lead orchestrator's context exceeds 70%, inform the user and suggest /compact or spawn the next round with a forked subagent to get clean context.

### Cost Visibility
After each round, report: findings found, findings fixed, findings rejected, cumulative rounds. The human can decide whether to continue or stop.

## Constraints

- **All fixes on the audit branch.** Never main.
- **Fresh agents each round.** No memory leakage.
- **Every finding needs instance fix AND class fix.**
- **Post-convergence regression tests are mandatory.**
- **All files inside the project directory.** Never /tmp.
- **Cost visibility every round.** Human can stop the loop.
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