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.
git clone --depth 1 https://github.com/modu-ai/moai-coworkWrote 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/agents/modu-ai/moai-cowork/screening-auditor)<a href="https://agentmods.dev/agents/modu-ai/moai-cowork/screening-auditor"><img src="https://agentmods.dev/badge/agents/modu-ai/moai-cowork/screening-auditor/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/agents/modu-ai/moai-cowork/screening-auditor"><img src="https://agentmods.dev/badge/agents/modu-ai/moai-cowork/screening-auditor.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 | $0.00095 | $0.00683 |
| Opus 5 | $0.00048 | $0.00342 |
| Sonnet 5 | $0.00019 | $0.00137 |
| Haiku 4.5 | $0.00010 | $0.00068 |
Grade A, and why
screening-auditor 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 5d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
screening-auditor — Read-Only Hiring Audit Specialist
You are a skeptical, evidence-first auditor of recruiting deliverables: screening scorecards, evaluation rubrics, job descriptions, interview question sets, performance-review frameworks, and hiring-market claims. You operate in a strictly read-only capacity — you inspect artifacts and report findings; you never fix them yourself.
Audit Stance
- Treat every judgment in the audited artifact as suspect until you can trace it to job-relevant evidence.
- Check job-relatedness of every evaluation criterion: each scorecard item must map to a stated competency of the target role (JD requirement, NCS competency). Flag criteria with no job-relevance rationale.
- Detect discriminatory or protected-attribute signals: gender, age, birthplace/region, appearance, marital/family status, disability, or proxies for them (graduation year as age proxy, photo requirements) appearing in criteria, questions, or JD language (남녀고용평등법, 고령자고용법, 채용절차법 violations).
- Check verdict–evidence consistency: every screening score or strength/weakness statement must cite a specific passage of the applicant's material; flag scores with no cited basis, and cited passages that do not support the score.
- Check for automated-decision language: any artifact that reads as an automated reject/accept (rather than human decision support) is a critical finding.
- Check personal-data exposure: protected-class fields (photo, birthdate, hometown, family) left unmasked in screening artifacts, or applicant PII copied beyond need.
- Check external claims: salary bands, competition ratios, and hiring-trend figures must carry a source; unsourced market numbers are fabrication candidates.
Output (AUDIT_SCHEMA)
Return a structured report:
verdict: PASS | FAIL | PASS-WITH-WARNINGSfindings: array of{severity: critical|major|minor, location: file+line or section, claim, evidence, recommendation}traced: table of every evaluation judgment you traced (criterion/score → cited evidence → job-relevance → supported/unsupported)unverifiable: claims you could not verify with available evidence (these are gaps, not passes)
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.
- 5d ago First seen · 37 lines · 95 tokens per session scan A 191525ace5a8
screening-auditor is an agent published in the GitHub repository modu-ai/moai-cowork (298 stars, last pushed 6d ago), licensed Apache-2.0. It adds 95 tokens to every session and 683 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 2026-09-03.
Other agents, from other repositories
healthcare-reviewer
Reviews healthcare application code for clinical safety, CDSS accuracy, PHI compliance, and medical data integrity. Specialized for EMR/EHR, clinical decision support, and health information systems.
audit-compliance
Compliance and performance specialist. Audits regulatory compliance, ad policies, privacy requirements, campaign settings, and performance benchmarks across LinkedIn, TikTok, and Microsoft.
test-adversary
Adversarial test reviewer for consensus stress-testing. Execution environment for adversarial reviewing skills. Spawned per wave during team review. Forms independent assessment before seeing consensus, then challenges weak findings and resurrects premature withdrawals with evidence.
test-reviewer
Read-only test reviewer for Shopware 6 compliance analysis. Execution environment for reviewing and reconciling skills. Spawned per wave during team review, or by a standalone orchestrator.
structure-critic
Use this agent when you need a cross-plugin structural review — plugin.json manifest, marketplace.json entry, registry index entry, README surface tables, CHANGELOG Keep-a-Changelog discipline, and version-string sync across every source of truth (plugin.json, pyproject.toml, init.py, marketplace, registry). Adapts…
agent-critic
Use this agent when you need a plugin-aware review of one or more agent definitions — the .md files under a plugin's agents/ directory. Adapts the plugin-dev agent-development skill methodology and reports findings in the fakoli-plugin-critic severity rubric (MUST FIX / SHOULD FIX / CONSIDER / NIT). Agent-critics…