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 rse/ase --skill ase-meta-reviewgit clone --depth 1 https://github.com/rse/aseWrote 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/rse/ase/ase-meta-review)<a href="https://agentmods.dev/skills/rse/ase/ase-meta-review"><img src="https://agentmods.dev/badge/skills/rse/ase/ase-meta-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/skills/rse/ase/ase-meta-review"><img src="https://agentmods.dev/badge/skills/rse/ase/ase-meta-review.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 | $0.00064 | $0.02076 |
| Opus 5 | $0.00032 | $0.01038 |
| Sonnet 5 | $0.00013 | $0.00415 |
| Haiku 4.5 | $0.00006 | $0.00208 |
Grade A, and why
ase-meta-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@${CLAUDE_SKILL_DIR}/../../meta/ase-control.md @${CLAUDE_SKILL_DIR}/../../meta/ase-skill.md @${CLAUDE_SKILL_DIR}/../../meta/ase-getopt.md
$ARGUMENTS
Procedure
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Determine whether there are staged changes at all by running the corresponding command (taken exactly as given) and capturing its output - the bare list of staged file names - into . This is a lightweight gate; the full diff is fetched by the sub-agent in STEP 2, so capturing only the file-name list here is sufficient:
git diff --cached --name-only HEAD
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The project source artifacts are classified as a black box, so the user does not want the staged changes scrutinized or their findings surfaced. Skip the entire review investigation: do not invoke the
Agenttool and do not read any change, set to the empty list, set toSKIPPED (boxing: black), set to a one-line neutral restatement of the change intent derived solely from STEP 1, and proceed directly to STEP 3.First, use the following to give a hint on this step:
Dispatch the review investigation to a sub-agent via the
Agenttool so that no investigation details leak into the user-visible transcript. The sub-agent performs the silent reading, the read-only repository probing, and the critique; only its final structured return value is consumed here.For this, invoke exactly once the tool:
Agent( description: "Review Investigation", subagent_type: "ase:ase-meta-review", prompt: "Review the staged changes.", run_in_background: false )Parse the single result message of the
Agenttool as a JSON object, set to itssummaryfield (a single crisp sentence reconstructing the change's intent), and set to itsfindingsfield (a list).Then derive the overall from : set to
REJECT - DEMANDS CHANGESif any finding in has aseverityfield ofHIGH; otherwise set toAPPROVE. The verdict is derived before the severity floor below, so the floor only affects which findings are rendered, never the verdict.Then determine the effective severity floor : define the ordinal rank
LOW=1,MEDIUM=2,HIGH=3, start from (defaultLOW), and - if is equalgrey- raise toMEDIUMwhenever its current rank is belowrank(MEDIUM)(grey boxing surfaces only material findings of severityMEDIUMand above). The floor affects only which findings are rendered, never the derived above.
What ships with it
1 file 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.
- 10d ago First seen · 211 lines · 64 tokens per session scan A 74fe83ddfea1
ase-meta-review is a skill published in the GitHub repository rse/ase (48 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 2,076 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 2026-08-30.
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