Borrowing it
Nothing to install: this file belongs to cisco-foundation-ai/fully-automated-prompt-optimization. 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/cisco-foundation-ai/fully-automated-prompt-optimization/main/.claude/commands/eval-runner.mdgit clone --depth 1 https://github.com/cisco-foundation-ai/fully-automated-prompt-optimizationWrote 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/cisco-foundation-ai/fully-automated-prompt-optimization/eval-runner)<a href="https://agentmods.dev/commands/cisco-foundation-ai/fully-automated-prompt-optimization/eval-runner"><img src="https://agentmods.dev/badge/commands/cisco-foundation-ai/fully-automated-prompt-optimization/eval-runner/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/commands/cisco-foundation-ai/fully-automated-prompt-optimization/eval-runner"><img src="https://agentmods.dev/badge/commands/cisco-foundation-ai/fully-automated-prompt-optimization/eval-runner.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.00550 |
| Opus 5 | $0.00000 | $0.00275 |
| Sonnet 5 | $0.00000 | $0.00110 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
eval-runner 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 9d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
description: > Run tenant evaluations and return score summaries. TRIGGER when: user wants to run an eval, test a prompt variant, check eval scores, execute an eval config, compare variant performance, or see evaluation results. DO NOT TRIGGER when: user is analyzing existing results (use optimization agent), creating synthetic data (use synthetic-samples), or editing prompts directly.
Eval Runner
Overview
Run a tenant evaluation config and return a concise summary plus the output directory path.
Quick Start
- Ensure provider credentials are available (for Baseten,
BASETEN_API_KEY). - Create a local eval config from the tracked template (configs are ephemeral and ignored):
mkdir -p tenants/<tenant_id>/configs
cp docs/templates/eval-config.template.json tenants/<tenant_id>/configs/local-<run-name>.json
- Run the helper script:
python scripts/eval/run_eval_and_summarize.py \
--config tenants/<tenant_id>/configs/local-<run-name>.json
This runs python -m hephaestus.cli eval --config ... and prints the evaluation summary plus the output directory.
Common Variations
- Run directly via CLI:
python -m hephaestus.cli eval --config tenants/<tenant_id>/configs/local-<run-name>.json
- Override output directory without editing your local config:
python scripts/eval/run_eval_and_summarize.py \
--config tenants/<tenant_id>/configs/local-<run-name>.json \
--output-dir tenants/<tenant_id>/evals/tmp/<run-name>
- Switch config for another prompt variant or dataset:
python scripts/eval/run_eval_and_summarize.py \
--config tenants/<tenant_id>/configs/local-<other-run>.json
Notes
- Output locations come from
output_dirin config (or--output-diroverride) and includesummary.md,results.jsonl, andrun_config.json. - Eval configs should remain local-only in
tenants/<tenant_id>/configs/and are not committed. hephaestus.cli eval --dry-runis intentionally disabled in this repo.
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.
- 9d ago First seen · 75 lines · 0 tokens per session scan A 36859cb0ddaf
eval-runner is a command published in the GitHub repository cisco-foundation-ai/fully-automated-prompt-optimization (107 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 550 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 2026-08-30.
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