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.
npx skills add Nagiliant/Genesis-Legacy-V2 --skill genesis-a2git clone --depth 1 https://github.com/Nagiliant/Genesis-Legacy-V2Wrote 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/skills/nagiliant/genesis-legacy-v2/genesis-a2)<a href="https://agentmods.dev/skills/nagiliant/genesis-legacy-v2/genesis-a2"><img src="https://agentmods.dev/badge/skills/nagiliant/genesis-legacy-v2/genesis-a2/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/skills/nagiliant/genesis-legacy-v2/genesis-a2"><img src="https://agentmods.dev/badge/skills/nagiliant/genesis-legacy-v2/genesis-a2.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 | $0.00039 | $0.00584 |
| Opus 5.5 | $0.00016 | $0.00234 |
| Sonnet 5.5 | $0.00008 | $0.00117 |
| Haiku 4.5 | $0.00004 | $0.00058 |
Grade A, and why
A2 — Spec 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 1mo 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A2 — Spec Review (FR/AC Compliance)
The mechanical compliance check. A2 walks every Functional Requirement (FR) and every Acceptance Criterion (AC) in the master spec and renders a binary verdict — Pass or Fail — against the implementation, with evidence. It makes no judgment about code quality (that is A3), direction (A4), or architecture (A1). Exhaustive and non-judgmental: each requirement either is satisfied by the code or it is not.
Inputs
spec.md(required — the source of all FRs/ACs) · all micro specs in scope · the actual code files they reference- The constitution · prior audit reports for this scope (e.g. the A1 report) for cumulative context · the project mode
Process
- Build the requirement checklist: extract every FR and AC that applies to this scope (for a group, the FRs/ACs its micro specs cover).
- Scan each file against each requirement — an exhaustive file-by-file pass. Produce a per-requirement verdict (Pass/Fail) with specific evidence.
- Review the scan for accuracy — correct false positives and false negatives, add context. (Two stages: a fast exhaustive pass, then a careful review pass.)
- (Brownfield) same File-Operations-table scoping and Inherited/Introduced classification as A1.
- Write the report to
audits/{scope}-a2.md: a coverage table listing every FR/AC with Pass/Fail and its evidence, a finding per failure with reasoning trace, and an overall verdict.
Discipline
A2 is binary and evidence-bound. A well-formed finding cites (1) the exact FR/AC ID with its wording, (2) the implementation evidence that fails it, and (3) a Pass/Fail verdict with no ambiguity. If a requirement is itself ambiguous, A2 flags the ambiguity rather than guessing intent — it never invents a passing or failing interpretation to resolve unclear spec language.
Shared machinery
Finding format, the zero-tolerance loop (loops to zero findings), and conviction scoring are shared across all lenses — see docs/the-audit-system.md. A2 may run alongside A1, but A3 still waits on A1 being clean.
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.
- 1mo ago First seen · 39 lines · 39 tokens per session scan A 045cd62f5996
A2 — Spec Review is a skill published in the GitHub repository Nagiliant/Genesis-Legacy-V2 (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 584 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
code-reviewer
Review completed implementation batches for spec compliance and code quality. Invoke after execution batches complete, before merging, or when a review gate is reached in the workflow.
arrow-maintenance
Navigation and audit overlay for linked-intent development. Use when working with docs/arrows/ — orienting via index.yaml, auditing spec-to-code coherence, detecting reverse orphans and drift, splitting/merging/renaming/re-parenting segments. Dual-mode: ambient guidance when the overlay is present…
review-depth
Experimental declared review depth for linked-intent development. Use when a LID project's instruction file declares a review depth in prose (e.g. 'Review depth - I review through LLD; below that, consolidate to one review') or the user asks to batch phase reviews, consolidate stops, or let go below a phase depth.…
bidirectional-differential
Audit coherence across an arrow of intent by running two parallel fresh Claude sessions — one reconstructs code from a single EARS, the other reconstructs the EARS from stripped code — then classifies the drift between them. Use when the user invokes /differential-audit, asks to audit EARS-to-code drift for a feature…
code-simplifier
Always-active simplicity rules: no speculative abstractions, one job per function, max 30 lines, flat over nested with early returns, descriptive names, comments explain why.
critical-review
4-phase adversarial review protocol: pre-flight analysis, adversarial execution check, self-correction loop, and [VALIDATION] report.