Auditing Progress

Overview

Runs after every iteration as part of the planning cycle. Verifies behavior evidence quality in three tiers using parallel adversarial review (PAR) — two paired auditor subagents evaluate the same work in parallel with competitive framing.

The audit answers: "Does durable, reusable evidence exist at the correct seam for every externally observable behavior this iteration touched?"

When to Use

Invoked by iterative-development after every running-an-iteration call, before picking the next iteration.

Audit Process

1. Partition the audit into three tiers

Read the per-epic requirement files in docs/superpowers/iterations/requirements/, docs/superpowers/iterations/behavior-scenarios.md, and docs/superpowers/iterations/behavior-corpus.md:

• Tier 1 — Deep evidence: stories marked done:ITER-<current> and scenarios added or updated in this iteration. Audit every AC and its proof obligation thoroughly.
• Tier 2 — Impacted behavior: all existing scenarios whose owning stories had code changes in this iteration (even if those stories were completed in earlier iterations). Verify the scenarios still pass.
• Tier 3 — Sentinel corpus: all scenarios with run cadence sentinel in the behavior corpus. Compare against the pre-iteration baseline from running-an-iteration step 3.

2. Dispatch paired auditor subagents (PAR)

Following the PAR methodology in skills/shared/parallel-adversarial-review.md:

1. Build the auditor prompt using auditor-subagent-prompt.md. Include ALL THREE tiers:
   • Tier 1: full story cards with proof obligations + new/changed scenario cards
   • Tier 2: impacted scenario cards + their current test results
   • Tier 3: sentinel scenario IDs + baseline results + current results
2. Wrap in competitive framing from skills/shared/par-reviewer-wrapper.md
3. Dispatch TWO auditor subagents in parallel
4. Wait for both to return

3. Aggregate findings

Following PAR aggregation rules:

• Same finding from both auditors → one finding, high confidence
• Finding from only one auditor → separate finding, still actionable
• Severity disagreement → take the more severe assessment, always fix it

4. Process results

• If gaps found (any AC fails, evidence is too weak, sentinel regression detected):
  • For AC failures: append gap stories to requirements/ (status pending) or flip existing stories back from done to pending
  • For weak evidence: create evidence-improvement stories (add scenario, strengthen seam)
  • For sentinel regressions: create regression-fix stories with CRITICAL priority
  • Revise roadmap.md to add a follow-up iteration for the gaps
• If clean (all tiers pass, evidence is adequate):
  • The iteration is confirmed done
  • Return clean signal to the orchestrator

5. Return control

Return the audit result (clean or gaps) to the orchestrator. The orchestrator decides whether to loop or terminate.

Quick Reference

References

• skills/shared/parallel-adversarial-review.md — PAR methodology
• skills/shared/par-reviewer-wrapper.md — competitive framing wrapper
• skills/shared/behavior-evidence-formats.md — scenario and proof obligation formats
• auditor-subagent-prompt.md — auditor-specific prompt template