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 oaustegard/claude-skills --skill gatinggit clone --depth 1 https://github.com/oaustegard/claude-skillsWrote 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/oaustegard/claude-skills/gating)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/gating"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/gating/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/oaustegard/claude-skills/gating"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/gating.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00137 | $0.02922 |
| Opus 5.5 | $0.00055 | $0.01169 |
| Sonnet 5.5 | $0.00027 | $0.00584 |
| Haiku 4.5 | $0.00014 | $0.00292 |
Grade A, and why
gating 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gating
A gate is a check that blocks. Its only job is to go red when it should.
The characteristic failure is not a wrong check — a wrong check gets noticed. It is a check that cannot fail, which reports PASS forever and is indistinguishable from a working one from the outside. That is what makes this different from ordinary testing: the object under suspicion is the check.
When NOT to use this skill
Scope is ONE check and whether it can be made to fail.
| Situation | Use |
|---|---|
| Sequence several steps with branches and retries | flowing |
| Run the repo's existing suite | run it |
| Decide what to test at all | this skill has no opinion; that is design |
A gate is a thing that goes red. If nothing here can go red, there is no gate to audit.
The three obligations
Every gate owes these. A gate missing any of them is not yet a gate.
1. An anchor outside your own code. Something the check compares against
that your implementation did not produce: a published constant, a closed-form
answer, a conservation law, a degenerate case with a known result, an
independent implementation. A check that compares this run to the last run only
ever tells you the code still does what it did. See references/anchors.md.
2. A known-bad it demonstrably rejects. Break the subject the way it would plausibly break, run the gate, confirm red. Until you have done this you have not shown the gate works — you have shown it runs. This is the obligation people skip, because a passing gate feels like evidence.
Two things about known-bads that are easy to get wrong:
- Validate it at the configuration it will run in. A case tuned on a small
or fast setting can stop being bad at full size. An "untrained" grid built
from one Lloyd iteration was genuinely zero-gain at m=2/K=16 and earned a
real +0.10 dB at m=8/K=65536, where one iteration relocates ~63,000 empty
cells toward the mode. It passed the fast gate and certified nothing about
the real one. This matters more than it sounds, because
mutate.pyneeds a fast gate variant and it is tempting to validate everything there. - Measure its reach. One known-bad is the floor, not the goal. Name which
checks it exercises (
known_bad(..., covers=(...))); the harness prints the checks no known-bad reaches. An audited gate had a single known-bad covering 1 of 8 checks — and the check its whole result rested on accepted the same bad case.
What ships with it
6 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 First seen · 213 lines · 137 tokens per session scan A 3fed62334d9e
gating is a skill published in the GitHub repository oaustegard/claude-skills (157 stars, last pushed yesterday), licensed MIT. It adds 137 tokens to every session and 2,922 once invoked, about $0.0005 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 2026-08-30.
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