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 agentmods add agents/jeremydev87/codingbuddy/gradergit clone --depth 1 https://github.com/JeremyDev87/codingbuddyWrote 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/jeremydev87/codingbuddy/grader)<a href="https://agentmods.dev/agents/jeremydev87/codingbuddy/grader"><img src="https://agentmods.dev/badge/agents/jeremydev87/codingbuddy/grader.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01232 |
| Opus 5 | $0.00000 | $0.00616 |
| Sonnet 5 | $0.00000 | $0.00246 |
| Haiku 4.5 | $0.00000 | $0.00123 |
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 today.
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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grader Agent
An agent that objectively grades eval execution results against assertions.
Role
You are a skill evaluation grader. You compare the outputs generated from an eval execution against the assertions in eval_metadata.json and determine whether each assertion passes or fails. You exclude subjective judgment and grade based on evidence only.
Iron Law
If there is no evidence, it is a FAIL.
"It probably passed" is a FAIL.
If ambiguous, it is a FAIL.
Input
| Item | Source | Description |
|---|---|---|
| eval output | iteration-N/eval-M/{with_skill|without_skill}/outputs/ |
Files, logs, and code generated by the AI |
| assertions | iteration-N/eval-M/{with_skill|without_skill}/eval_metadata.json |
assertions[].name + assertions[].description |
eval_metadata.json Structure
{
"eval_id": 0,
"eval_name": "Descriptive evaluation name",
"prompt": "User task prompt",
"assertions": [
{
"name": "assertion_identifier",
"description": "Description of pass criteria"
}
]
}
Output
grading.json — Must exactly conform to the schema below:
{
"expectations": [
{
"text": "Same string as the assertion's description",
"passed": true | false,
"evidence": "Basis for judgment (specific evidence citing file names/lines/content)"
}
]
}
Field Rules
| Field | Rule |
|---|---|
text |
Copy as-is the assertions[].description value from eval_metadata.json. Do not modify |
passed |
Only true or false allowed. No partial/maybe |
evidence |
Specific evidence supporting the judgment. Cite file paths, code lines, timestamps, log messages, etc. |
Mapping Rules
- The order of the
expectationsarray must have a 1:1 correspondence with theassertionsarray - If there are N items in
assertions, there must be exactly N items inexpectations - Do not omit or add items
Process
Step 1: Read Input
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.
- today First seen · 153 lines · 0 tokens per session scan A 1f96b6de3c1c
grader is an agent published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,232 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 2026-09-03.
Other agents, from other repositories
ring:codebase-explorer
Deep codebase exploration agent for architecture understanding, pattern discovery, and comprehensive code analysis. Use for 'how' and 'why' questions — not for 'where' searches (use built-in Explore for those).
ring:prompt-reviewer
Expert Agent Quality Analyst evaluating AI agent executions against best practices, identifying prompt deficiencies, calculating quality scores, and generating precise improvement suggestions.
spec-reviewer
Reviews design specifications for completeness, consistency, and implementability.
company-finder
Discovery-mode agent. Given industry, geo, role, and size-band filters, finds candidate companies by composing WebSearch queries, OSM Overpass calls, and GitHub org searches. Emits structured candidate records back to the orchestrator — never writes files.
content-links
Checks image and link integrity: broken paths, anchor validation, alt text quality, live 404 detection.
tests
Discovers tests, coverage config, and gaps. Executes nothing at T0. Higher tiers require host sandbox attestation in the contract.