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-finalgit 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-final)<a href="https://agentmods.dev/skills/nagiliant/genesis-legacy-v2/genesis-final"><img src="https://agentmods.dev/badge/skills/nagiliant/genesis-legacy-v2/genesis-final/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-final"><img src="https://agentmods.dev/badge/skills/nagiliant/genesis-legacy-v2/genesis-final.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 | $0.00055 | $0.00794 |
| Opus 5 | $0.00028 | $0.00397 |
| Sonnet 5 | $0.00011 | $0.00159 |
| Haiku 4.5 | $0.00006 | $0.00079 |
Grade A, and why
Final — The F-Pass 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 11d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Final — The F-Pass
After all groups are accepted, the feature gets one final, feature-wide audit pass. The per-group audits caught drift within a group; the F-pass catches what only shows up when the whole feature is viewed at once — cross-group inconsistency, integration gaps, and quality that no single group owned.
Gate: every group must be accepted in approvals/master.json before the F-pass begins. This is the mandatory next step after the last group-accept — never skip straight to closure.
The F-pass is seven stages, run in order. The same Double Gate physics apply: the deeper stages cannot begin until the consistency stage (F1) is clean.
| Stage | Lens | Scope |
|---|---|---|
| F1 | Design + master-spec consistency (A1, feature-wide) | all groups |
| F2 | Spec review — FR/AC compliance (A2, feature-wide) | every FR/AC in the spec |
| F3 | Polish (A3, feature-wide) | all code/content |
| F4 | North Star direction (A4, feature-wide) | the whole feature vs the vision |
| F5 | Web audit (A5, feature-wide) | the whole stack |
| F6 | Dreamland | dream perfection, then make it real |
| F7 | Simulation | realistic scale testing |
F1–F5 — the lenses, feature-wide
Run each lens exactly as its per-group skill defines it (/genesis-a1…/genesis-a5), but scoped to the entire feature rather than one group. Findings, reports, the zero-tolerance loop, and conviction are identical — see docs/the-audit-system.md. Reports go to audits/final-f{N}.md. F3 cannot start until F1 is at zero findings.
F6 — Dreamland
Step back from what was built and describe the feature at its dream-perfect best — not constrained by what exists, not by the spec, just: what would make this genuinely excellent? Then take each dream and ask whether it can be made real now. Every realizable dream becomes a finding (fix now) or a tracked design input. Dreamland is where the kit reaches past "meets the spec" toward "is actually great." Record the report to audits/final-f6.md.
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.
- 11d ago First seen · 49 lines · 55 tokens per session scan A 8cbe89f0d5fc
Final — The F-Pass is a skill published in the GitHub repository Nagiliant/Genesis-Legacy-V2 (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 55 tokens to every session and 794 once invoked, about $0.0003 per session on Opus 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
repo-consistency-sweep
Proactive defect-class detection that handles the lower-value half of code review (per Bacchelli and Bird 2013) so human reviewers stay focused on design, intent, and knowledge transfer. Catches convention drift, ordering bugs, type-safety gaps, security and multi-tenant invariants (CWE-grounded), and operability…
pr-feedback-ingest
Turn PR feedback (Greptile, CI, bots, humans) into a structured traceable backlog aligned with TASKSTATE.md, DECISIONS.md, and IMPLEMENTATIONPLAN.md so the next execution step can be a narrow implement-approved-slice or a small planning touch without losing alignment. Corrective scope only. Use when a PR is open or…
review-hard
Review the current task changes for real correctness, safety, and maintainability risks before slice closure or PR prep, and recommend the smallest safe next step. Surfaces meaningful issues (not cosmetic feedback); not a replacement for external review systems. Returns no-op when the review would not materially…
verify-against-rubric-fleet
Orchestrator-workers generalization of verify-against-rubric to N=many artifacts against ONE locked rubric. Dispatches N stateless Sonnet sub-agents in parallel; each receives ONE artifact + the SAME rubric + read-only tools (no TASKSTATE, no DECISIONS, no prior history); returns structured per-criterion verdict.…
atom-audit-fleet
Orchestrator-workers variant of atom-audit. Dispatches N Haiku workers (3-5 atoms each) to audit every atom under packages/design-system/src/atoms/ in parallel against COMPONENTGUIDELINES.md rules; merges per-worker rows into ATOMAUDIT.md table. Use when atom count >= 6 (per cost-effectiveness threshold) AND…
graphql-contract-review
Review a GraphQL schema and a Backend-for-Frontend (BFF) contract BEFORE implementation, against a GraphQL-specific checklist: schema shape and nullability (null-bubbling), errors-as-data unions, N+1 and DataLoader, query cost and depth limits, cursor-connection pagination, federation entity ownership, breaking-change…