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 skills add 0xmariowu/Autosearch --skill routergit clone --depth 1 https://github.com/0xmariowu/AutosearchWrote 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/0xmariowu/autosearch/router)<a href="https://agentmods.dev/skills/0xmariowu/autosearch/router"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/router/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/skills/0xmariowu/autosearch/router"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/router.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 | $0.00047 | $0.01099 |
| Opus 5 | $0.00023 | $0.00549 |
| Sonnet 5 | $0.00009 | $0.00220 |
| Haiku 4.5 | $0.00005 | $0.00110 |
Grade A, and why
autosearch:router 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 10d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Routing Policy
When the runtime AI picks up an autosearch research task, do not try to read every leaf SKILL.md. Follow this three-step routing:
- Identify 1–3 groups from the query intent. Use the keyword hints below as a first pass; use the domain + scenario tags on each group index for ambiguity.
- Read only those group indexes (
references/groups/<group>.md). Each group index lists its leaf skills with one-line triggers and suggested model tier. - Pick 3–8 leaf skills from the matched groups. Read their
SKILL.mdonly when you're about to call them.
Do not enumerate every leaf skill to the main model. That defeats the entire progressive-disclosure design and burns tokens.
Group Selection Hints
Content surface
| If the query mentions… | Pick group |
|---|---|
| 小红书 / 抖音 / B站 / 微博 / 知乎 / 播客 / 快手 / 雪球 / V2EX | channels-chinese-ugc |
| 36kr / CSDN / 掘金 / InfoQ 中文 / 微信公众号 | channels-cn-tech |
| paper / arxiv / citation / benchmark / 论文 / survey / openreview | channels-academic |
| github / repo / code / issue / npm / pypi / huggingface | channels-code-package |
| crunchbase / 融资 / producthunt / G2 review | channels-market-product |
| stack overflow / hacker news / dev.to / reddit | channels-community-en |
| twitter / X / linkedin / 职业 / career | channels-social-career |
| 一般网页 / 搜索引擎 / tavily / exa / ddgs / searxng / rss | channels-generic-web |
| 视频 / 字幕 / 转录 / podcast / youtube | channels-video-audio |
Tool surface
| If the task is… | Pick group |
|---|---|
| Fetch a URL, render JS, run interactive browser, download media | tools-fetch-render |
| Clarify user intent, decompose a task, recall known info, gene queries | workflow-planning |
| Normalize, rerank, anti-cheat, extract dates, score with LLM, apply rubrics | workflow-quality |
| Assemble context, extract knowledge, build knowledge map, synthesize report | workflow-synthesis |
| Track outcomes, auto-evolve skills, create new skills, capture/compact experience | workflow-growth |
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- __init__.py 347 B runs code
- references/groups/channels-academic.md 1.9 KB
- references/groups/channels-chinese-ugc.md 1.9 KB
- references/groups/channels-cn-tech.md 1.2 KB
- references/groups/channels-code-package.md 1.2 KB
- references/groups/channels-community-en.md 1.3 KB
- references/groups/channels-generic-web.md 1.5 KB
- references/groups/channels-market-product.md 1.1 KB
- references/groups/channels-social-career.md 1.2 KB
- references/groups/channels-video-audio.md 1.6 KB
- references/groups/tools-fetch-render.md 1.8 KB
- references/groups/workflow-growth.md 2.3 KB
- references/groups/workflow-planning.md 2.0 KB
- references/groups/workflow-quality.md 1.6 KB
- references/groups/workflow-synthesis.md 1.7 KB
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.
- 10d ago First seen · 88 lines · 47 tokens per session scan A 4037cb9a1c35
autosearch:router is a skill published in the GitHub repository 0xmariowu/Autosearch (44 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 1,099 once invoked, about $0.0002 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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