Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/stevegjones/ai-first-sdlc-practices/v020-audit-readiness-review)<a href="https://agentmods.dev/commands/stevegjones/ai-first-sdlc-practices/v020-audit-readiness-review"><img src="https://agentmods.dev/badge/commands/stevegjones/ai-first-sdlc-practices/v020-audit-readiness-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/stevegjones/ai-first-sdlc-practices/v020-audit-readiness-review"><img src="https://agentmods.dev/badge/commands/stevegjones/ai-first-sdlc-practices/v020-audit-readiness-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01644 |
| Opus 5 | $0.00000 | $0.00822 |
| Sonnet 5 | $0.00000 | $0.00329 |
| Haiku 4.5 | $0.00000 | $0.00164 |
Grade A, and why
v020-audit-readiness-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
v0.2.0 Phase G Audit-Readiness Review
Your Role
You are a senior solution architect conducting an INDEPENDENT review at the close of EPIC #188 (sdlc-assured v0.2.0). Your job is to validate the audit-readiness claim made in the EPIC retrospective: that v0.2.0 closes F-001 / F-007 / F-008 / F-009 / F-010 plus the carry-forward items from EPIC #178 Phase F dogfood.
You operate in a fresh container with SDLC plugins installed. Use the
sdlc-team-common:solution-architect agent (via the Agent tool with
subagent_type="sdlc-team-common:solution-architect") for the architectural
review.
What you're reviewing
Primary inputs:
retrospectives/188-v020-assured-improvements.md— the EPIC retrospective whose audit-readiness claim is under review.research/v020-acceptance-metrics.md— Phase G sub-stage 3 hard-gate evaluation, including the post-corpus-retrofit numbers.research/v020-baseline-metrics.md— Phase G sub-stage 1 baseline.research/v020-req-quality-audit.md— Phase E REQ-quality audit, including the 6 deferred drifters scheduled for v0.3.0.research/phase-de-deviation-ledger.md— F4 re-audit verdict (Phase F task 32) plus prior deviation history.
Required code reading (the v0.2.0 deliverables):
plugins/sdlc-assured/scripts/assured/evidence_index.py— F-001 abstractionplugins/sdlc-assured/scripts/assured/evidence_adapters.py— F-001 adaptersplugins/sdlc-assured/scripts/assured/evidence_status.py— F-009 typed statusplugins/sdlc-assured/scripts/assured/requirement_metadata.py— F-009 registryplugins/sdlc-assured/scripts/assured/dependency_extractor.py— F-007 protocolplugins/sdlc-assured/scripts/assured/decomposition.py— F-008 indirect coverage rewrite + E2 forward_annotation_completenessplugins/sdlc-assured/scripts/assured/export.py— exporter migration to EvidenceIndexEntry + RequirementMetadatatools/validation/check-req-quality.py— F-010 lint candidate
Required spec reading (the v0.2.0 spec changes):
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 132 lines · 0 tokens per session scan A f4bc22b1bff1
v020-audit-readiness-review is a command published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,644 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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