Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/swarm-ai-research/swarm/benchmark)<a href="https://agentmods.dev/commands/swarm-ai-research/swarm/benchmark"><img src="https://agentmods.dev/badge/commands/swarm-ai-research/swarm/benchmark.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 | $0.00000 | $0.00654 |
| Opus 5 | $0.00000 | $0.00327 |
| Sonnet 5 | $0.00000 | $0.00131 |
| Haiku 4.5 | $0.00000 | $0.00065 |
Grade A, and why
benchmark 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 6d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/benchmark
Run the SWARM Track A multi-agent benchmark suite (standardized task conditions, governance presets, behavioral assessments) and auto-compile results to PDF — use when evaluating agent behavior against reproducible baselines before paper submission, or to generate comparison data across model variants. Distinct from /run_scenario (single scenario, single seed), /sweep (parameter grid without analysis), and /full_study (end-to-end pipeline including paper scaffolding).
Usage
/benchmark [preset] [options]
Presets
| Preset | Tasks | Conditions | Description |
|---|---|---|---|
quick |
50 | baseline only | Fast smoke test |
baseline |
500 | baseline only | Full baseline benchmark |
adversarial |
500 | adversarial only | Adversarial conditions only |
full |
500 | all | Baseline + adversarial (default) |
Options
--no-pdf- Skip PDF compilation--no-commit- Skip committing artifacts--difficulty N- Set task difficulty (0-1, default 0.5)--seed N- Set random seed
Implementation
When user invokes /benchmark, run:
# Parse preset
PRESET="${1:-full}"
TASKS=500
FLAGS=""
case "$PRESET" in
quick)
TASKS=50
;;
baseline)
# baseline only (default, no extra flags)
;;
adversarial)
FLAGS="--adversarial-only"
;;
full)
FLAGS="--adversarial"
;;
esac
# Run benchmark
python scripts/run_swarm_track_a.py --tasks $TASKS --difficulty 0.5 $FLAGS
# Get output directory from last line
RUN_DIR=$(ls -td runs/swarm_collate/track_a_* | head -1)
echo "Run completed: $RUN_DIR"
# Compile PDF unless --no-pdf
if [[ ! " $* " =~ " --no-pdf " ]]; then
cd "$RUN_DIR"
tectonic paper.tex 2>/dev/null || /opt/anaconda3/bin/tectonic paper.tex
open paper.pdf
fi
# Commit unless --no-commit
if [[ ! " $* " =~ " --no-commit " ]]; then
cd -
git add "$RUN_DIR"
git commit --no-verify -m "Add Track A benchmark run: $(basename $RUN_DIR)"
fi
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.
- 6d ago First seen · 87 lines · 0 tokens per session scan A 98dc47e06e78
benchmark is a command published in the GitHub repository swarm-ai-research/swarm (41 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 654 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.
Other commands, from other repositories
tma1-peer
List recent sessions on this project by agent — peers (Codex, OpenClaw, Copilot CLI) or your own.
test
Run tests with intelligent package filtering and reporting.
eval-merge
Use the Read tool to load .skill-compass/{skill-name}/manifest.json. Verify.
video
Create a design based on video.
good
Write good creative & smart copy [GOOD].
speckit.git.validate
Validate current branch follows feature branch naming conventions.