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 instructions/benchflow-ai/skillsbench/agents-mdgit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/instructions/benchflow-ai/skillsbench/agents-md)<a href="https://agentmods.dev/instructions/benchflow-ai/skillsbench/agents-md"><img src="https://agentmods.dev/badge/instructions/benchflow-ai/skillsbench/agents-md.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 | $0.00692 | $0.00692 |
| Opus 5 | $0.00346 | $0.00346 |
| Sonnet 5 | $0.00138 | $0.00138 |
| Haiku 4.5 | $0.00069 | $0.00069 |
Grade A, and why
skillsbench AGENTS.md 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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SkillsBench
Benchmark for evaluating how well AI agents use skills. 87 default runnable task definitions, expanding toward 100+.
Commands
uv tool install "benchflow>=0.6.2,<0.7"
uv sync --locked
bench tasks init <task-id>
bench tasks check tasks/<task-id>
bench eval run --tasks-dir tasks/<task-id> --agent oracle --sandbox docker
bench eval run --tasks-dir tasks/<task-id> --agent claude-agent-acp --model <model> --skill-mode with-skill --skills-dir tasks/<task-id>/environment/skills/
bench eval run --tasks-dir tasks/<task-id> --agent claude-agent-acp --model <model> --skill-mode no-skill
bench skills list
bench skills eval <skill-dir> # evaluate a skill against its evals/evals.json
Task Layout
SkillsBench tasks are native BenchFlow task.md packages:
tasks/<task-id>/
task.md # YAML frontmatter + human-written prompt body
environment/
Dockerfile # Container setup
skills/ # Domain skills (generalizable, not task-specific)
oracle/
solve.sh # Oracle (human-written, derives answers via computation)
verifier/
test.sh # Pytest runner, writes reward.txt
test_outputs.py # Outcome-based assertions
Default runnable tasks live in tasks/. Credential-dependent or
integration-incompatible tasks live in tasks-extra/ and are included in
integration sweeps only when --no-default-excludes is passed.
Rules
task.mdprompt body andoracle/solve.shmust be human-written — never generate these- Never mention skill names in the task prompt
- Skills must be generalizable and reusable, not task-specific
- Tests verify outcomes, not process — don't check which tools were used
- Oracle must derive answers through computation, not hardcode them
- No fake scenarios, no synthetic data when real data exists
- Prefer tasks without external API dependencies
task.mdfrontmattermetadatamust validate against taxonomy.yaml — pickcategoryfrom the controlled list, plussubcategory,task_type,modality,interface,skill_type. See taxonomy.md for the codebook and decision rules. CI runs.github/scripts/lint_taxonomy.pyon every PR that touchestasks/**/task.md.
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 · 59 lines · 692 tokens per session scan A 11d227e867ba
skillsbench AGENTS.md is an instructions file published in the GitHub repository benchflow-ai/skillsbench (1,745 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 692 tokens to every session, about $0.0035 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.
Other instructions, from other repositories
ClawBench AGENTS.md
AGENTS.md instructions for TIGER-AI-Lab/ClawBench, covering clawbench -- agent context, what this is, project structure, setup and 2. configure at least one model.
openbench AGENTS.md
Instructions for minghinmatthewlam/openbench, covering openbench — agent context, local execution context, what openbench is, execution ownership and product goals (the two things we are building toward).
argus-validation-benchmarks CLAUDE.md
Instructions for pensar-x/argus-validation-benchmarks, covering project overview, what you're building, the goal, success criteria and what is apex?.
agent-belt AGENTS.md
AGENTS.md instructions for jfrog/agent-belt, covering agent-belt - guide for ai coding agents, 1. what this is, 2. setup & first verification, 3. where to start (by task) and 4. design principles.
inferbench CLAUDE.md
Claude Code instructions for JoniMartin27/inferbench, covering instrucciones para claude code en este proyecto, antes de tocar nada, lo que no debes hacer (load-bearing), schemas de optimización son por motor, no uniformes and no simules motores.
OpenChainBench AGENTS.md
AGENTS.md instructions for ChainBench/OpenChainBench, covering this is not the next.js you know and branch workflow.