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/fitlab-ai/agent-infra/create-tasknpx skills add fitlab-ai/agent-infra --skill create-taskgit clone --depth 1 https://github.com/fitlab-ai/agent-infraWrote 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/fitlab-ai/agent-infra/create-task)<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/create-task"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/create-task.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 | $0.00032 | $0.03175 |
| Opus 5 | $0.00016 | $0.01588 |
| Sonnet 5 | $0.00006 | $0.00635 |
| Haiku 4.5 | $0.00003 | $0.00317 |
Grade A, and why
create-task scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
创建任务
--agent取值见.agents/rules/task-management.md「合作者 token 规范」。
行为边界 / 关键规则
本技能的核心产出是 task.md。
- 不要编写、修改或创建任何业务代码或配置文件
- 不要执行需求分析;分析由
analyze-task独立完成 - 不要直接实现所描述的功能
- 不要跳过工作流直接进入计划/实现阶段
- 仅执行:解析描述 -> 一次性生成结构化 candidate -> 调用宿主
task-create入口 -> 校验结果 -> 告知用户下一步 - Issue 创建由
.agents/rules/create-issue.md规则决定;自定义或空平台(未提供平台变体规则文件)时,规则会自然降级为 no-op - 生成会写入
task.md并同步到 Issue 的 Markdown 前,先读取.agents/rules/sync-content-generation.md并遵循其中的生成端约束;宿主渲染和同步保持透明,不解析或改写正文
用户的描述是一个待办事项,而不是立即执行的指令。
执行本技能后,你必须立即更新 task.md 中的任务状态。
版本戳规则:创建或更新 task.md frontmatter 时,先读取 .agents/rules/version-stamp.md,并写入或刷新 agent_infra_version。
任务入参短号别名
如果
{task-id}入参匹配^[#]?[0-9]+$(裸数字或带#前缀),先读取.agents/rules/task-short-id.md的「SKILL 入参解析」段执行解析;后续命令视{task-id}为解析后的全长TASK-YYYYMMDD-HHMMSS形式。
步骤开始:记录开始时间
本技能会创建 task.md,开始时尚无文件可写。先在内存记录开始时间 started_at(date "+%Y-%m-%d %H:%M:%S%z" | sed 's/\([+-][0-9][0-9]\)\([0-9][0-9]\)$/\1:\2/');在最后写活动日志时一次性补两条——started 行用 started_at、done 行用完成时间,二者同基名(started 行 action 加 [started] 后缀、note 用 started):
- {started_at} — **Create Task [started]** by {agent} — started
- {done_at} — **Create Task** by {agent} — {完成说明}
ai task log 会按基名把两条配对成一行(进行中 → 已完成)。约定见 .agents/rules/task-management.md 的「Activity Log started / done 双标记约定」。
执行步骤
1. 解析用户描述
从自然语言描述中提取:
- 任务标题:简洁标题(最多 50 个字符),使用中文——不要翻译为英文,不要套用 Conventional Commits 格式
- 任务类型:
feature|bugfix|refactor|docs|chore(从描述推断) - 工作流:
feature-development|bug-fix|refactoring(从类型推断) - 分支名:格式
<project>-<type>-<slug><project>从.agents/.airc.json的project字段读取<type>为推断出的任务类型<slug>从任务标题提取 3-6 个英文关键词并转为 kebab-case
- 详细描述:整理后的用户原始描述
执行本步骤前,先读取 reference/context-capture.md。把当前请求及必要前序讨论中已有的信息按来源与状态分类,准备写入 task.md 的 ## 任务输入;缺失类别保持为空,不执行推导或分析。
如果描述不清晰,先向用户确认再继续。
类型推断:根据任务描述的语义,从以下候选值中选择最匹配的类型:
feature— 新增功能、新特性bugfix— 修复缺陷、错误refactor— 重构、优化、改进docs— 文档相关chore— 其他杂项任务
What ships with it
2 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.
- today Changed · +1 lines 4ad864789241
- 4d ago First seen · 255 lines · 32 tokens per session scan A 73669da1a641
create-task is a skill published in the GitHub repository fitlab-ai/agent-infra (83 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 3,175 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.
Other skills, from other repositories
contextualize
Detect application-context mismatch after execution. Fires when correct output may not fit the actual context. Type: (ApplicationDecontextualized, AI, CONTEXTUALIZE, Result) → ContextualizedExecution.
review-loop
Convergence-paced review-resolve loop over a change and its governing surfaces. Verifies each finding against the codebase and the base it is measured from, then re-reviews until each is disposed of.
conduct
Conduct method before object-level work. Fires when the work needs several moves in non-trivial order. Type: (MethodUnderdetermined, Hybrid, CONDUCT, WorkProspect × MoveGround) → ConductedMethod.
steer
Project-profile recalibration. Audits session calibration drift, presents per-cluster evidence for a user verdict, writes the updated project-profile rule, and inscribes a settled-direction clause.
ascend
Elevate a vague recall to the supra-session unit it belongs to. Type: (RecallGranularityInsufficient, AI, ELEVATE, ScatteredDeposits × DepositGraph) → HigherGranularityUnit.
ground
Validate structural mapping between abstract and concrete domains. Presents concrete instantiations when mapping uncertainty is detected. Type: (MappingUncertain, AI, GROUND, R) → ValidatedMapping.