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 commands/tyejcoleman/tokenroom/run-evalsgit clone --depth 1 https://github.com/tyejcoleman/tokenroomWrote 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/commands/tyejcoleman/tokenroom/run-evals)<a href="https://agentmods.dev/commands/tyejcoleman/tokenroom/run-evals"><img src="https://agentmods.dev/badge/commands/tyejcoleman/tokenroom/run-evals.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 | $0.00017 | $0.00326 |
| Opus 5 | $0.00009 | $0.00163 |
| Sonnet 5 | $0.00003 | $0.00065 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
run-evals 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.
What it actually says
Run the behavioral evals for: $ARGUMENTS
Per ADR-9, any change claiming to affect model behavior (stamp wording, SKILL.md policy, fit_check verdict semantics, handoff rendering) needs eval evidence before merging.
- Pick the harness:
eval/(v0 — cheap single-shot planning probes; fastest iteration),eval/v1/(execution-level with live simulated budgets; the headline numbers),eval/v2-continuity/(post-compaction resume). Read the harness README first. - Use the harness's setup scripts to generate cells/prompts — never hand-edit prompts per-cell (determinism is the comparison's validity).
- Run matched naive/equipped (or before/after wording) cells with the same model. Small models are fine for directional signal; say so in the writeup.
- Grade from ARTIFACTS (commits, suites, journals) per the harness RUBRIC.md — never from agent self-reports. Never offer the desired behavior as a labeled slot in prompts (demand characteristics).
- Write results to the harness's
results/as a dated markdown file: matrix, verdicts, AND an honest caveats section. Weak results get published too — see the G2-sim writeup for the expected tone.
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.
- 4d ago First seen · 24 lines · 0 tokens per session scan A 02b48661aeb4
run-evals is a command published in the GitHub repository tyejcoleman/tokenroom (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 326 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 2026-08-31.
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