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 nick-railsback/skill-engine --skill applygit clone --depth 1 https://github.com/nick-railsback/skill-engineWrote 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/nick-railsback/skill-engine/apply)<a href="https://agentmods.dev/skills/nick-railsback/skill-engine/apply"><img src="https://agentmods.dev/badge/skills/nick-railsback/skill-engine/apply/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/nick-railsback/skill-engine/apply"><img src="https://agentmods.dev/badge/skills/nick-railsback/skill-engine/apply.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 | $0.00036 | $0.00935 |
| Opus 5.5 | $0.00014 | $0.00374 |
| Sonnet 5.5 | $0.00007 | $0.00187 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
apply 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apply
Promote a reviewed proposal into the live contextualizer. Atomic-rename per file. Preserve the REVIEW.md audit trail in the live tree. Refuse to run when the proposal has not been signed off, when the sign-off is reject, or when more than one Step 3 box is ticked.
When to invoke
After /skill-engine:review <name> has run, the user has filled Step 1 of REVIEW.md, re-run review to populate Step 2, ticked verdict boxes on each disagreement (optional — for the engine's own read; the engine does not consume these), and ticked exactly one Step 3 box (reviewed or provisional).
Resolving <name> and <install>
Same resolution as /skill-engine:review: <name> is the slug without the -context suffix; bare invocation works when exactly one *-context.proposed/ exists under <install>. See review/SKILL.md § Resolving <name> for the full rule.
Pre-promotion gates
Run these in order; any failure halts the apply and exits non-zero without
mutating either tree: the manifest exists and parses, REVIEW.md exists
and parses, the review loop actually ran (not just a ticked box — two
literal-content checks against Step 1/Step 2), exactly one Step 3 box is
ticked and it isn't reject, and the live tree hasn't changed since
staging (per-entry content-hash comparison against the manifest's
sha_before/sha_after). The exact checks, halt messages, and per-status
hash rules are in
references/pre-promotion-gates.md.
Promotion, review-state and preamble reconciliation
Promote file-by-file from the manifest (resume-safe per entry), then —
before moving the audit trail — write research/review-state.json (the
persisted sign-off ledger) and reconcile the provisional-mode preamble
block in the live SKILL.md, then move REVIEW.md + manifest.json into
the live .review/ and remove the emptied proposed directory. The
per-status promotion rules, the ledger schema, and the preamble's exact
delimiter format and four reconciliation cases are in
references/promotion-and-reconciliation.md.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed c80a7581ef1d
- 1mo ago First seen · 59 lines · 36 tokens per session scan A 101f406ef503
apply is a skill published in the GitHub repository nick-railsback/skill-engine (2 stars, last pushed 6d ago), licensed MIT. It adds 36 tokens to every session and 935 once invoked, about $0.0001 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.
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