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 haru0416-dev/quaere --skill quaere-auditgit clone --depth 1 https://github.com/haru0416-dev/quaereWrote 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/haru0416-dev/quaere/quaere-audit)<a href="https://agentmods.dev/skills/haru0416-dev/quaere/quaere-audit"><img src="https://agentmods.dev/badge/skills/haru0416-dev/quaere/quaere-audit/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/haru0416-dev/quaere/quaere-audit"><img src="https://agentmods.dev/badge/skills/haru0416-dev/quaere/quaere-audit.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 | $0.00146 | $0.04132 |
| Opus 5 | $0.00073 | $0.02066 |
| Sonnet 5 | $0.00029 | $0.00826 |
| Haiku 4.5 | $0.00015 | $0.00413 |
Grade A, and why
quaere-audit 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 9d 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Audit Loop
Iron Law
No security finding is confirmed without a falsifiable property, a reachable attacker-controlled path, a missing or failed guard, concrete impact, and a disconfirming false-positive pass.
This is the security version of evidence-gating. Dangerous APIs, scary strings, stale advisories, and pattern matches are leads, not findings. A finding becomes actionable only when the audit can show why the property should hold, where an attacker crosses a boundary, which sink/state/guard fails, what impact follows under the threat model, and what counter-evidence was checked. If any link is missing, classify it as potential, rejected, or inconclusive.
When to use
- Vulnerability discovery, security code review, bug bounty preparation, exploitability triage, or protocol/spec-grounded auditing.
- Auth/authz, tenant isolation, injection, parser, sandbox, cryptography, consensus, payments, secrets, SSRF, deserialization, supply-chain, cloud/config, or CI/CD security work.
- Security-sensitive PRs or incidents where false positives, unsafe probes, or stale external facts would be costly.
When NOT to use
- Pure dependency lookup or CVE freshness checks with no local exploitability analysis; use
quaere-groundingfirst. - Normal implementation after a vulnerability is already confirmed and a fix is authorized; use
quaere-execution. - General maintainability review, one-line known fixes, or shallow checklist-only reviews.
- Any task whose rules of engagement are missing and probing could affect third-party or production systems; stop and ask.
Handoff triggers (which skill comes after this one)
Audit coordinates other skills; hand off when the blocking question is not security-property mapping:
- Code intent, invariants, failure modes, or downstream connections are unclear →
quaere-semantic. - Current specs / CVEs / advisories / docs / cloud behavior / framework guidance / CLI behavior / bounty rules must be anchored →
quaere-grounding. - A subtle / disputed / security-sensitive candidate finding still needs proof before being confirmed →
quaere-evidence. - Safe PoC, regression test, or authorized fix is the next step →
quaere-execution.
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.
- 9d ago First seen · 270 lines · 146 tokens per session scan A c4efca8f4978
quaere-audit is a skill published in the GitHub repository haru0416-dev/quaere (5 stars, last pushed 1mo ago), licensed MIT. It adds 146 tokens to every session and 4,132 once invoked, about $0.0007 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
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analyzing-changes
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analyzing-security
Scans code for security vulnerabilities, detects dangerous patterns, and ensures security decisions are documented. Use when running security scans, auditing code, or checking for OWASP issues, injection risks, or sensitive data leaks. Automatically triggered on new modules, security-related changes, or post-refactor.
checking-code-quality
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pingfusi-review
Use Pingfusi proactively whenever a coding agent reaches a question it cannot settle with code, automated tests, documentation or search, or a local browser and needs real human judgment or real-world verification. Trigger even when the user does not mention Pingfusi for subjective choices about copy, design, clarity…
verifying-modules
Scans directory structure, detects missing documentation, and verifies code-doc synchronization. Use when checking module completeness, README presence, or DESIGN.md alignment. Automatically triggered after creating new modules.