SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
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 skills/benchflow-ai/skillsbench/constraint-parsernpx skills add benchflow-ai/skillsbench --skill constraint-parsergit 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/skills/benchflow-ai/skillsbench/constraint-parser)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/constraint-parser"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/constraint-parser.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 | $0.00011 | $0.00142 |
| Opus 5 | $0.00005 | $0.00071 |
| Sonnet 5 | $0.00002 | $0.00028 |
| Haiku 4.5 | $0.00001 | $0.00014 |
Grade A, and why
constraint-parser 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 5d 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
Constraint Parser
This skill parses the constraints from raw email text containing a meeting scheduling request.
Input
Raw email text containing a meeting scheduling request.
Instruction
Given the email text, extract the scheduling constraints: times or conditions that must or must not be met (e.g., specific time windows, unavailable days).
Example Output
{
"constraints": [
"Jan 5-7th 9:00am to 12:00pm",
"not available from 11:00am to 11:30am on Jan 6th"
]
}
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.
- 5d ago First seen · 26 lines · 11 tokens per session scan A e9a5ef0c9844
constraint-parser is a skill published in the GitHub repository benchflow-ai/skillsbench (1,745 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 11 tokens to every session and 142 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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