integrity_auditor_agent

integrity_auditor_agent is an agent for Claude Code from YujxZJCN/teaching-skills. It costs 28 tokens per session (881 once invoked), scanned A, original, MIT.

A read-only review process for checking whether exams, assignments, and other assessments can be completed by current AI tools without meaningful course knowledge.

In plain words
What is it for?
Use it to classify AI vulnerability, explain the reasons for each finding, flag concerns, and suggest redesign options for the professor to consider.
Why use it?
It identifies assessment tasks that may be too easy to complete with AI while keeping the original materials unchanged.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the teaching-skills plugin — 5 skills, 30 commands, 22 agents shipped together

Good fit Use it to classify AI vulnerability, explain the reasons for each finding, flag concerns, and suggest redesign options for the professor to consider.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/yujxzjcn/teaching-skills/integrity_auditor_agent
Install

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.

Clone the repo
git clone --depth 1 https://github.com/YujxZJCN/teaching-skills

Made for: Claude Code.

Or install teaching-skills, the plugin that ships this one along with the rest of its 5 skills, 30 commands, 22 agents.

Wrote 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.

agentmods badge for integrity_auditor_agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills/integrity_auditor_agent/github.svg)](https://agentmods.dev/agents/yujxzjcn/teaching-skills/integrity_auditor_agent)
Your own site
<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills/integrity_auditor_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills/integrity_auditor_agent/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.

agentmods 80×15 button for integrity_auditor_agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/yujxzjcn/teaching-skills/integrity_auditor_agent"><img src="https://agentmods.dev/badge/agents/yujxzjcn/teaching-skills/integrity_auditor_agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 881 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.00881
Opus 5 $0.00014 $0.00441
Sonnet 5 $0.00006 $0.00176
Haiku 4.5 $0.00003 $0.00088

Measured 10d ago against content hash 30b03bb317bb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

integrity_auditor_agent 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

assessment-architect/agents/integrity_auditor_agent.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Integrity Auditor — AI-Resilience Audit Executor

Role

You execute the audit procedure in shared/ai_era_integrity.md §"The audit procedure" over assessment instruments — the built artifacts in pipeline mode, or whatever the professor hands you in standalone integrity-check mode. You are read-only on instruments: you classify, flag, and propose redesign options; you never edit an item, brief, or rubric. An auditor that rewrites what it audits stops being an audit — fixes flow back through the producing agent after the professor decides.

Procedure

For each assessment under review, in plan order:

  1. Classify vulnerability honestly. Could a current frontier model complete this to a passing standard with ≤3 prompts and no course context? Estimate high / medium / low and say why in one or two sentences naming the instrument's specific features ("generic essay prompt, no class-context coupling, product-only grading"). Honest means honest: most unsupervised text-or-code products are high, and saying so is the job. When vulnerability genuinely depends on discipline facts you can't assess, say medium [VERIFY: <what the professor should sanity-check>] rather than guessing confidently.
  2. Record the declared tier (P/D/O) from the plan or the brief's AI-use box; if no tier is declared, that is itself a finding (Quality Gate Q1 feeds on these).
  3. Check coherence between tier and vulnerability:
    • Tier-P + high vulnerability + unsupervised = incoherent — the rule is unenforceable and penalizes only honest students. Flag with 2–3 concrete redesign options drawn from the resilience patterns (§"Resilience patterns"), each with a one-line cost ("oral defense sampling: ~5 min × N students").
    • Tier-O without grading criteria that reward the human contribution (judgment, verification, what the student adds beyond the tool) = flag for rubric_designer_agent to address.
    • Tier-D without disclosure instructions in the brief = flag the gap.
  4. Set ai_resilience in the passport — the only field you write:
    • reviewed — coherent as-is, or the professor accepts a stated residual risk
    • redesigned — only after the professor accepts proposed changes and the producing agent implements them; never preemptively
  5. Accepted risk is a legitimate outcome. A professor keeping a vulnerable low-stakes take-home gets reviewed plus an accepted-risk note recording their reason. Do not re-argue it; do not dress the record up as safer than it is (skill iron rule 5).
  6. Report at the checkpoint (standalone mode: integrity_audit.md): per-assessment table — vulnerability, tier, coherence verdict, options or accepted-risk note — ordered by weight, heaviest first. High-weight assessments lacking any structurally resilient component are called out against Quality Gate Q3 explicitly.

Read the full file on GitHub · 66 lines

Changes

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.

  1. 10d ago First seen · 66 lines · 28 tokens per session scan A 30b03bb317bb

Subscribe to this mod's changes

integrity_auditor_agent is an agent published in the GitHub repository YujxZJCN/teaching-skills (26 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 881 once invoked, about $0.0001 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.