Borrowing it
Nothing to install: this file belongs to Temikus/denkeeper. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Temikus/denkeeper/main/.claude/skills/judge-eval/SKILL.mdgit clone --depth 1 https://github.com/Temikus/denkeeperWrote 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/temikus/denkeeper/judge-eval)<a href="https://agentmods.dev/skills/temikus/denkeeper/judge-eval"><img src="https://agentmods.dev/badge/skills/temikus/denkeeper/judge-eval/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/temikus/denkeeper/judge-eval"><img src="https://agentmods.dev/badge/skills/temikus/denkeeper/judge-eval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.01952 |
| Opus 5.5 | $0.00019 | $0.00781 |
| Sonnet 5.5 | $0.00010 | $0.00390 |
| Haiku 4.5 | $0.00005 | $0.00195 |
Grade A, and why
judge-eval 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 2mo 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Judging a denkeeper eval run
Rubric version: v1 (2026-08-17)
You are the judge in a blinded A/B comparison. A denkeeper eval run executed every test case in a task set against two agent configurations — an incumbent and a candidate — through the real engine, with writes suppressed. Your job is to say which of two responses is better, without knowing which configuration produced either.
You never learn the assignment. Model, provider, variant name, cost, latency and token usage are withheld server-side. Do not speculate about them, and do not let a guess influence a verdict. If you find yourself reasoning about "this looks like a bigger model", stop and go back to the response.
Setup
The tools come from denkeeper's MCP server. The judging key needs exactly two scopes and nothing else:
denkeeper keys create judge --scopes eval:read,eval:write
A judge key with wider scopes can start runs and spend money; this one can read pairs and write verdicts, and that is all it should ever be able to do.
Add the server to Claude Code (adjust host and key):
claude mcp add --transport http denkeeper https://your-denkeeper/api/v1/mcp --header "Authorization: Bearer $DENKEEPER_JUDGE_KEY"
Tools
| Tool | What it does |
|---|---|
eval_run_status |
Run status, progress, pairs produced, items still pending |
eval_pending |
The queue. run_id scopes it; sample_n draws a random subset |
eval_get_pair |
One blinded item: prompt, notes, pinned history, Response A and B with tool traces |
eval_verdict |
Record {item_id, winner, dimensions, notes, rubric_version} |
eval_summary |
Unblinds: gate table, win-rate, per-category breakdown, verdict |
Each pair of responses is queued twice, with the presentation order swapped. Both items must be judged before the pair counts, and if your two verdicts name different sides the pair records as a tie — that is the position-bias control, and it only works if you judge each item on its own. Never try to recognise a pair you have already seen, and never look up your earlier verdict.
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.
- 2mo ago First seen · 166 lines · 48 tokens per session scan A 4de1f2c1b1bb
judge-eval is a skill published in the GitHub repository Temikus/denkeeper (15 stars, last pushed today), licensed Apache-2.0. It adds 48 tokens to every session and 1,952 once invoked, about $0.0002 per session on Opus 5.5. 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.
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