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.
git clone --depth 1 https://github.com/the-thinker0/math-skillWrote 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/the-thinker0/math-skill/ask)<a href="https://agentmods.dev/commands/the-thinker0/math-skill/ask"><img src="https://agentmods.dev/badge/commands/the-thinker0/math-skill/ask/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/the-thinker0/math-skill/ask"><img src="https://agentmods.dev/badge/commands/the-thinker0/math-skill/ask.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 | $0.00059 | $0.00217 |
| Opus 5.5 | $0.00024 | $0.00087 |
| Sonnet 5.5 | $0.00012 | $0.00043 |
| Haiku 4.5 | $0.00006 | $0.00022 |
Grade A, and why
ask 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 1mo 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
语言路由（内联）
判定主语言：看句式、动词、语气词的主框架。AI/数学/工程术语（attention、loss、routing 等）不计入语言判定。代码、路径、公式不计入。中英比例接近时沿用上一轮语言，无上下文默认中文。显式"用英文/用中文"优先。
- 中文主语言 → 读取
../SKILL.md（权威入口，可中英作答） - 英文主语言 → 读取
../SKILL.en.md（英文兼容入口） - 两者不同时加载
当前问题： $ARGUMENTS
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.
- 1mo ago First seen · 18 lines · 59 tokens per session scan A d92bea8f5a4f
ask is a command published in the GitHub repository the-thinker0/math-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 217 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
openehr-explain
One-stop router that explains or looks up any openEHR thing — auto-detects an archetype, a template, an RM/AM/BASE type, an RM structural concept, an ADL idiom, an AQL query or keyword, or a terminology code (replaces /archetype-explain, /template-explain, /type-spec, /rm-structure, /adl-idiom, /terminology).
srs-discussion
Draft or improve the Discussion section using: argument flow review → claim calibration → reviewer perspective.
srs-figures
Comprehensive quality control for all figures and tables: QC → captions → visual consistency → table design.
srs-gate
Run the revision quality gate on the current section or full manuscript. Used both after individual sections and as the final pre-submission check.
srs-intro
Draft or improve the Introduction section using the three-skill chain: benchmark positioning → section drafting → claim calibration.
srs-results
Draft or improve the Results section using: results writing → figure QC → claim calibration.