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/openanalystinc/10x-analyst/cleannpx skills add OpenAnalystInc/10x-analyst --skill cleangit clone --depth 1 https://github.com/OpenAnalystInc/10x-analystWrote 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/openanalystinc/10x-analyst/clean)<a href="https://agentmods.dev/skills/openanalystinc/10x-analyst/clean"><img src="https://agentmods.dev/badge/skills/openanalystinc/10x-analyst/clean.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 | $0.00017 | $0.01013 |
| Opus 5 | $0.00009 | $0.00507 |
| Sonnet 5 | $0.00003 | $0.00203 |
| Haiku 4.5 | $0.00002 | $0.00101 |
Grade A, and why
clean 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 123 lines · 17 tokens per session scan A 1722b71018b0
clean is a skill published in the GitHub repository OpenAnalystInc/10x-analyst (4 stars, last pushed 5mo ago), with no licence file. It adds 17 tokens to every session and 1,013 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 2026-08-31.
Other skills, from other repositories
pr-checklist
Use when opening or finalizing a GitHub PR for OpenMetadata. Walks through the repo PR template — linked issue, high-level design (for big PRs), unit/integration/Playwright tests + coverage, UI screen recording, and manual test steps — then drafts a fully-filled PR body and (optionally) creates the PR.
connector-standards
Load all OpenMetadata connector development standards into context. Use before building or reviewing connectors to ensure consistent patterns.
ppt-analysis
PPT (.pptx/.ppt) 全量解析。覆盖:所有 slide 文本/表格/图表提取、嵌入图片 caption、纯图片 slide 渲染识别、数据标签提取。.
dashboard-design
Use this skill first when the user wants to design or plan a dashboard, especially Vizro dashboards. Enforces a 3-step workflow (requirements, layout, visualization) before implementation. Activate when the user asks to create, design, or plan a dashboard. For implementation, use the dashboard-build skill after…
writing-playwright-tests
Redirect only — this skill was merged into playwright. Invoke playwright instead for Playwright E2E authoring guidance and the required lint gate.
trend-analysis
基于多维度数据进行分级评估与趋势预测,通过设定差异化增长率计算预测值,并生成对比可视化图表,适用于绩效评估、目标设定等场景。.