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 CCDawn/codex-skills --skill briefbound-competition-research-lifecyclegit clone --depth 1 https://github.com/CCDawn/codex-skillsWrote 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/ccdawn/codex-skills/briefbound-competition-research-lifecycle)<a href="https://agentmods.dev/skills/ccdawn/codex-skills/briefbound-competition-research-lifecycle"><img src="https://agentmods.dev/badge/skills/ccdawn/codex-skills/briefbound-competition-research-lifecycle/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/ccdawn/codex-skills/briefbound-competition-research-lifecycle"><img src="https://agentmods.dev/badge/skills/ccdawn/codex-skills/briefbound-competition-research-lifecycle.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 | $0.00049 | $0.00995 |
| Opus 5 | $0.00024 | $0.00498 |
| Sonnet 5 | $0.00010 | $0.00199 |
| Haiku 4.5 | $0.00005 | $0.00100 |
Grade A, and why
briefbound-competition-research-lifecycle 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 9d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Briefbound 竞赛科研全流程
目标
维护竞赛/benchmark 项目的阶段边界、事实源和跨阶段依赖,让当前最具体 owner 连续推进。它是全项目协调层,不重复执行研究、score、写作或工程流程。
Briefbound task contract
- Context Boundary: 竞赛规则、数据/metric、active baseline/evidence、当前阶段、关键 artifact、提交约束和截止时间。
- Output Contract: 当前阶段判断、跨阶段风险、一个 primary owner、阶段完成证据和下一阶段动作。
- Allowed Action: 读取项目事实源并协调当前阶段;具体实验、工程、审查和写作由最具体 owner 执行。
- Success Evidence: 规则/数据版本、baseline/实验记录、claim 来源、submission checklist 或外部反馈中的阶段必要证据。
- Stop Condition: 规则/metric/数据漂移、active evidence 冲突、关键提交要求未知、claim 无来源或继续会污染有效证据。
- Route Out: 当前阶段 owner、
briefbound-ai-research-loop、briefbound-score-loop、briefbound-research-rigor-review、工程 owner、briefbound-router或 BLOCKED。
统一调用契约
- 只处理 Briefbound task contract 范围;不匹配时回
briefbound-router或更具体 owner,复合任务不吞其他 owner。 - 用户可见内容默认中文,完成只报状态、产出、证据和剩余风险;代码、命令、路径、错误原文、API/协议、skill 名和枚举保留原样;Route Out 仅以 Briefbound task contract 为准,末行写
下一步建议: <一个具体动作>。
激活闸门
只有请求跨越至少两个阶段,或规则、数据、baseline、claim、submission 之间的依赖需要统一治理时进入。单次论文复现/消融用 AI Research,反复 metric 晋升用 Score Loop,关键 claim 审查用 Rigor Review,具体工程故障用对应工程 owner。
阶段地图
按项目实际情况映射,不强制创建八套 artifact:规则与目标 -> 数据/协议 -> baseline -> 研究实验 -> 证据综合/claim -> 提交或发布。
每次只维护:当前阶段、active truth、阻塞下一阶段的最小缺口、primary owner、完成证据。已有项目工件优先;缺少模板但不影响当前决策时继续,不为形式补文档。
协调规则
- 先读取最相关的规则、metric、数据版本、baseline、实验结果、claim map 或提交清单,不扫描所有阶段。
- 识别当前阶段及最早失效的上游证据;上游漂移时标记受影响下游为 stale 并回退修复。
- 选择一个能直接产生下一阶段必要证据的 primary owner。当前 owner 完成后,若下一阶段明确且已授权,连续路由,不逐阶段询问。
- AI Research 可以内部完成简单实验;只有反复晋升/榜单 lane 才下沉 Score Loop。普通 candidate gate 不经过 Rigor Review。
- 只有论文/对外 claim、方向转向、重要 best-known 结果或高成本投入才进入 Rigor Review。
- 并行只用于真正独立的 artifact 和写入面;不默认创建 3-6 lanes、worktree 或多 Agent。
Smoke/proxy 只用于可运行性、淘汰和排序,不替代正式目标评估。外部 leaderboard 是重要校准证据,但不能静默改变本地 protocol 或 claim 范围。
输出
阶段: <当前阶段>
- Active truth: <规则/数据/baseline/evidence>
- 关键缺口或漂移: <仅真实项>
- Primary owner 与产出:
- 阶段完成证据:
下一步建议: <一个具体动作>
跨会话或正式交接时才读取 references/lifecycle-reference.md 和 references/templates.md;需要校准典型阶段切换时读取 references/examples.md。普通推进不输出完整 lifecycle 表、Briefbound gate 或阶段菜单。
What ships with it
4 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.
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.
- 9d ago First seen · 60 lines · 49 tokens per session scan A 18f1c913d644
briefbound-competition-research-lifecycle is a skill published in the GitHub repository CCDawn/codex-skills (4 stars, last pushed 27d ago), licensed MIT. It adds 49 tokens to every session and 995 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 2026-08-31.
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