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 overflowy/herdr-adversarial-review --skill adversarial-reviewgit clone --depth 1 https://github.com/overflowy/herdr-adversarial-reviewWrote 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/overflowy/herdr-adversarial-review/adversarial-review)<a href="https://agentmods.dev/skills/overflowy/herdr-adversarial-review/adversarial-review"><img src="https://agentmods.dev/badge/skills/overflowy/herdr-adversarial-review/adversarial-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/overflowy/herdr-adversarial-review/adversarial-review"><img src="https://agentmods.dev/badge/skills/overflowy/herdr-adversarial-review/adversarial-review.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 | $0.00092 | $0.01013 |
| Opus 5 | $0.00046 | $0.00507 |
| Sonnet 5 | $0.00018 | $0.00203 |
| Haiku 4.5 | $0.00009 | $0.00101 |
Grade A, and why
adversarial-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 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Review
scripts/reviewer.sh drives the whole reviewer lifecycle - it builds the prompt,
splits a herdr pane, launches safecodex, submits, waits through permission
prompts, and verifies the output file. Your job is the two things it can't do:
state the intent and verify the findings.
<skill-dir> below is this skill's directory (shown when the skill loads) -
substitute its absolute path.
The reviewer runs interactively in the split pane, so the user can watch it, approve prompts, or steer it.
1. State the intent, then start
Determine what to review (default: the working diff) and - critically - the intent: what the author is trying to achieve. The reviewer challenges whether the work achieves the intent well, not whether the intent is correct. If you can't infer the intent, ask.
Write it to a file (one or two sentences, always in English), show it to the user, and start:
cat > /tmp/intent.md <<'EOF'
<what the author is trying to achieve>
EOF
<skill-dir>/scripts/reviewer.sh start --intent-file /tmp/intent.md --diff
Target selection:
--diff- working diff (git diff HEAD) plus untracked files. The default.--file PATH- review a plan, doc, or specific file. Repeatable.- Both - e.g. a diff reviewed against the plan it implements.
--timeout MS- overall budget (default 900000).
Never paste diffs or file contents yourself; the flags collect them.
Run start with the Bash tool's run_in_background: true. A review can outlast
the foreground Bash timeout cap (which would kill the wait loop mid-review), and
backgrounding keeps the session free while the reviewer works - pick up the
output when the background task completes. ask is quick enough to run in the
foreground.
On success it prints REVIEW_FILE=.... On failure it exits non-zero with a
diagnostic and a tail of the reviewer pane - relay that and stop; the pane stays
open for inspection.
If the reviewer hits a permission prompt, the script notifies the user, prints a
BLOCKED note, and keeps waiting - tell the user to approve it in the pane.
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.
- 11d ago First seen · 108 lines · 92 tokens per session scan A 1e93f99d13d7
adversarial-review is a skill published in the GitHub repository overflowy/herdr-adversarial-review (7 stars, last pushed 1mo ago), licensed MIT. It adds 92 tokens to every session and 1,013 once invoked, about $0.0005 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.
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