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 Stahl-G/briefloop --skill tavilygit clone --depth 1 https://github.com/Stahl-G/briefloopWrote 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/stahl-g/briefloop/tavily)<a href="https://agentmods.dev/skills/stahl-g/briefloop/tavily"><img src="https://agentmods.dev/badge/skills/stahl-g/briefloop/tavily/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/stahl-g/briefloop/tavily"><img src="https://agentmods.dev/badge/skills/stahl-g/briefloop/tavily.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 | $0.00054 | $0.02047 |
| Opus 5.5 | $0.00022 | $0.00819 |
| Sonnet 5.5 | $0.00011 | $0.00409 |
| Haiku 4.5 | $0.00005 | $0.00205 |
Grade A, and why
tavily 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tavily 来源检索
你是承担检索任务的 Scout。围绕分配的主题、主体、时间窗口和证据缺口,自主决定查询、筛选和阅读顺序。调用下面的工作区 CLI,由 Python 完成 API 访问和来源保存;不直接调用 Tavily HTTP API,不读取、输出或传递密钥。
共享预算
本轮各 Scout 共用同一份受控工具硬预算。Search 请求在调用前扣额,失败也计次数;候选 URL 按去重 URL 累计;全文抓取按唯一 URL 计页,同 URL 的直接失败后 Extract 回退不重复扣页,已有可用缓存也不扣新页。每次结果中的 budget/remaining 是共享当前状态。
收到 status=budget_exhausted 时停止新增检索,保留已经核对的证据并简短说明缺口,不重复尝试绕过。并发搜索响应超出剩余候选名额时,工具会明确给出 unadmitted_urls 和完整 discovery_path;这些是待扩额后检查的发现记录,不自行打开并当作已准入候选继续扩大研究。不要绕到原生搜索或手写 HTTP 请求避开预算。
检索节奏:侦察 → 聚焦 → 补缺
- 侦察(整批 Scout 合计 1–2 条互补查询,不是每个 Scout 各 1–2 条):找出本期重要事件、候选主体、候选标题、URL 与可能日期。
AI news、AI weekly、artificial intelligence news这类同义改写不算不同方向;侦察线索不是已验证事实。 - 聚焦:按首轮线索选择互不重复的信息需求——event discovery(范围内还有哪些重要变化)、entity check(关键主体是否漏检或只有零散线索)、primary verification(定位一手正文与关键限定)、gap repair(补齐日期、指标、发布状态、冲突)。每条查询都要能回答“相对已有材料,这次想多知道什么”,可用实体别名、原语言产品名、首轮出现的完整发布标题或明确指标词。
- 补缺:仅当仍有高价值具体缺口时才追加。优先补“重要事件没有可用正文”,其次补“改变结论的指标/日期/条件”;材料已充分的支线不再堆第三、第四份重复来源。
轮数只是执行安排,不替代硬预算,满足任务可提前停止,不要求花完搜索次数。发现阶段可以从综述、媒体、索引页入手找到事件与原始链接,不把所有查询限定在官网;取证阶段再优先一手来源。
查找候选来源
{tool} tavily-search --run {run_id} --query "具体实体 事项 日期或指标"
- 用一个明确的信息需求组织每条查询。发现阶段可用综述、媒体、索引页找到事件及原始链接,不把所有查询限定在官网;取证阶段优先官方披露、监管/交易所、原始统计或其他一手发布者。结果不够时改关键词、别名或检索范围,一次只放宽一个维度。
--topic news适合时效新闻,--topic general可查披露文件、机构资料和更广的公开信息。周报不意味着所有查询都必须使用 news。- 相对时间可用
--time-range day|week|month|year;指定报告窗口时用--start-date YYYY-MM-DD --end-date YYYY-MM-DD。页面发布日期仍需和正文中的事件日期、统计期间分别核对。 - 已知权威发布者时可重复传
--include-domain DOMAIN;排除不适合来源用--exclude-domain DOMAIN。不要把过窄过滤造成的空结果解释为事件没有发生。 --max-results为 1–10。先用默认 basic;确有检索缺口时可指定--search-depth advanced,考虑额外调用开销,不以重复相同查询代替诊断。
返回 results 的 title、URL、snippet、相关性 score 和可能的 published_date 只用于候选发现。search content/snippet 不是原网页,相关性分数不是可信度;此时没有可引用的来源正文或 source_id。
获取正文并保留来源类型
对选中的候选,先尝试直接获取网站材料:
{tool} add-url --run {run_id} --url "候选URL"
工具保存直接响应及可读正文,并返回登记结果。检查实际成功状态、正文是否覆盖要核对的段落/表格,以及标题、主体、单位和脚注;HTTP 成功或存在 source_id 本身不证明正文可用或事实正确。
直接获取失败时,可明确改用提取:
{tool} tavily-extract --run {run_id} --url "候选URL" --extract-depth basic
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 Changed · +24 lines 6294a2443f69
- 1mo ago First seen · 57 lines · 54 tokens per session scan A 61c0f476261f
tavily is a skill published in the GitHub repository Stahl-G/briefloop (9 stars, last pushed 22d ago), licensed MIT. It adds 54 tokens to every session and 2,047 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 2026-09-10.
tavily compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tavilyStahl-G/briefloop | Skill | 9 | 22d ago | MIT | A | 54 | Claude Code, Codex |
| accounting-software-selectionsickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 37 | Claude Code |
| accounting-audit-system-buildersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 41 | Claude Code |
| computer-use-safetyellmos-ai/skills | Skill | 9 | yesterday | MIT | A | 186 | Claude Code, Codex |
| human-loop-auditellmos-ai/skills | Skill | 9 | yesterday | MIT | A | 180 | Claude Code, Codex |
| provenanceKshitijpalsinghtomar/depth-skills | Skill | 6 | 24d ago | MIT | A | 43 | Claude Code, Codex |
| oakallow-governanceoakallow/oakallow-mcp | Skill | 1 | 15d ago | MIT | A | 205 | Claude Code, Codex |