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 skills add DataLab-atom/EvoAny --skill write-experimentgit clone --depth 1 https://github.com/DataLab-atom/EvoAnyWrote 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/datalab-atom/evoany/write-experiment)<a href="https://agentmods.dev/skills/datalab-atom/evoany/write-experiment"><img src="https://agentmods.dev/badge/skills/datalab-atom/evoany/write-experiment.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 5.1 | $0.00026 | $0.00955 |
| Opus 5 | $0.00013 | $0.00477 |
| Sonnet 5 | $0.00005 | $0.00191 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
write-experiment 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 7d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/write-experiment — Experiment Chapter Writing
D2: Experiment chapter generation — transforms B-layer experiment results and figures into a comprehensive experimental section.
Purpose
Read the B-layer experiment results (metrics, figures) and the C-layer forest contributions, and generate a well-structured Experiment section in LaTeX format.
Usage
/write-experiment <forest_id> [--venue <venue_name>]
Examples:
/write-experiment exp-2024-run-01 --venue NeurIPS/write-experiment my-forest --venue CVPR
Prerequisites
Before running this skill, ensure:
- B-layer experiments have been executed and results collected
- Viz figures have been generated — call
viz_generateduring Phase 2 Step 4 of/research-loopto generate ablation curves, score distributions, and contribution heatmaps before proceeding. Ifresearch/figures/is empty, generate them now:- Call
viz_generateon each confirmed hypothesis - Call
viz_polishfor publication-quality rendering - Record the output paths for reference in the chapter
- Call
- The forest has at least one contribution recorded
Behavior
Step 1: Gather Experiment Data
- Read the forest:
research_get_forest(forest_id)— get contributions and experiment nodes - Collect all experiment results:
- Metrics from
bench_runoutputs - Figure paths from
viz_generateoutputs (stored inresearch/figures/) - Polished figures from
viz_polishoutputs
- Metrics from
- List all figures: check
research/figures/directory- If no figures exist: call
viz_generatenow for ablation curves and main result plots - Call
viz_polishon each figure before including in the chapter
- If no figures exist: call
Step 2: Organize Results
Group results into categories:
- Main Results — primary performance comparisons
- Ablation Studies — contribution of individual components
- Sensitivity Analysis — robustness to hyperparameters
- Additional Experiments — any supplementary results
Step 3: Synthesize the Experiment Chapter
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.
- 7d ago First seen · 120 lines · 26 tokens per session scan A b8a30e584422
write-experiment is a skill published in the GitHub repository DataLab-atom/EvoAny (37 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 26 tokens to every session and 955 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 2026-08-30.
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