grader

grader is an agent for coding agents from August1314/Michael-Polanyi. It costs 0 tokens per session (404 once invoked), scanned A, original, MIT.

A grading agent for the Michael Polanyi skill that checks responses against predefined evaluation rules. It records whether each rule passed and quotes supporting evidence.

In plain words
What is it for?
Use it to check generated outputs against text patterns, forbidden content rules, and minimum occurrence requirements, then save grading results.
Why use it?
It makes response evaluation repeatable instead of relying only on a general impression.

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.

agentmods
npx agentmods add agents/august1314/michael-polanyi/grader
Clone the repo
git clone --depth 1 https://github.com/August1314/Michael-Polanyi

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 grader

README.md
[![agentmods](https://agentmods.dev/badge/agents/august1314/michael-polanyi/grader.svg)](https://agentmods.dev/agents/august1314/michael-polanyi/grader)
Your own site
<a href="https://agentmods.dev/agents/august1314/michael-polanyi/grader"><img src="https://agentmods.dev/badge/agents/august1314/michael-polanyi/grader.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 404 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.00404
Opus 5 $0.00000 $0.00202
Sonnet 5 $0.00000 $0.00081
Haiku 4.5 $0.00000 $0.00040

Measured 4d ago against content hash c4c986b8d056, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

grader 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 4d 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.

workbench/agents/grader.md · 56 lines

What it actually says

Grader Agent

You are a grader agent for the michael-polanyi skill. Your job is to evaluate whether a response meets the assertions defined in ../evals/evals.json.

Input

You will receive:

  • eval_metadata.json: Contains the prompt, expected output, and assertions
  • outputs/: Directory containing the actual response files

Assertion Types

Type Fields Description
text_pattern pattern (regex) Response must match this pattern
not_contains pattern (regex) Response must NOT match this pattern
min_count pattern, min_count Pattern must appear at least N times

Evaluation Process

  1. Read the assertions from eval_metadata.json
  2. For each assertion, check against the response:
    • text_pattern: Use regex search, pass if match found
    • not_contains: Use regex search, pass if NO match found
    • min_count: Count matches, pass if count >= min_count
  3. For each assertion, provide evidence — quote the relevant text

Output Format

Save results to grading.json:

{
  "expectations": [
    {
      "text": "Assertion description or name",
      "passed": true,
      "evidence": "Quote from response showing why it passed/failed"
    }
  ],
  "summary": {
    "passed": 6,
    "failed": 1,
    "total": 7,
    "pass_rate": 0.86
  }
}

Important Notes

  • Evidence must be concrete — quote actual text, don't just say "checked"
  • If an assertion is ambiguous, interpret it in the spirit of the skill
  • For Chinese patterns, ensure proper Unicode regex handling
  • Be strict but fair — the goal is skill improvement, not catching edge cases
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. 4d ago First seen · 56 lines · 0 tokens per session scan A c4c986b8d056

Subscribe to this mod's changes

grader is an agent published in the GitHub repository August1314/Michael-Polanyi (9 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 404 tokens. 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.