block-task

block-task is a skill for Claude Code, Codex from fitlab-ai/agent-infra. It costs 52 tokens per session (1,866 once invoked), scanned A, original, MIT.

A task-management skill that marks a referenced task as blocked and records why work cannot continue.

In plain words
What is it for?
Use it when a task is waiting on a missing dependency, access, decision, external team, or an unresolved technical or requirements problem.
Why use it?
It keeps stalled work visible and explains what is preventing progress, instead of leaving the task in an unclear active state.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/fitlab-ai/agent-infra/block-task
Any agent
npx skills add fitlab-ai/agent-infra --skill block-task
Clone the repo
git clone --depth 1 https://github.com/fitlab-ai/agent-infra

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for block-task

README.md
[![agentmods](https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/block-task.svg)](https://agentmods.dev/skills/fitlab-ai/agent-infra/block-task)
Your own site
<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/block-task"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/block-task.svg" alt="Measured on agentmods" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,866 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.01866
Opus 5 $0.00026 $0.00933
Sonnet 5 $0.00010 $0.00373
Haiku 4.5 $0.00005 $0.00187

Measured 2d ago against content hash 2ba4c58e412c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

block-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 2d 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.

.agents/skills/block-task/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

标记任务阻塞

--agent 取值见 .agents/rules/task-management.md「合作者 token 规范」。

行为边界 / 关键规则

  • 本命令更新任务元数据并物理移动任务目录
  • 仅在确实无法继续时才阻塞 —— 如果是可以克服的困难,先尝试解决

使用场景

  • 技术问题:无法解决的 Bug、缺少依赖、基础设施问题
  • 需求问题:需求不明确、规格冲突、待定决策
  • 资源问题:缺少访问权限、等待外部团队、被其他任务阻塞
  • 需要决策:待定的架构决策、需要利益相关者批准

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

任务上下文解析

入口可省略 task ref;显式 task scope 仅接受 --task <ref>-t <ref>,不再解释位置 task ref。保留其余业务操作数后调用 agent-infra-internal task-context resolve {task-scope}{task-scope} 为空或 task flag 之一。只读取结构化结果的 taskId,后续把 {task-id} 绑定为完整 TASK-YYYYMMDD-HHMMSS。解析失败时透传非零退出码,不自行扫描任务。

解析任务引用,并确认任务位于本技能支持的状态或目录且存在 task.md;无法定位时按未找到任务处理并停止。

步骤开始:本地生命周期边界

确认前置条件后,由步骤 3 的单次 lifecycle intent 原子写入 started/done 日志、基础元数据、目录转移和短号释放;本步骤不得提前手工写入其中任一项。

执行步骤

1. 验证任务存在

检查任务是否存在于 .agents/workspace/active/{task-id}/

注意:{task-id} 格式为 TASK-{yyyyMMdd-HHmmss},例如 TASK-20260306-143022

如果未找到,检查其他目录并告知用户。

2. 分析阻塞原因

阻塞之前,彻底分析:

  • 具体的问题是什么?
  • 根本原因是什么?
  • 已经尝试了哪些解决方案?
  • 需要什么帮助或信息才能解除阻塞?

3. 执行本地生命周期意图

agent-infra-internal task-lifecycle {task-id} block --agent {standard-agent-token} \
  --reason "{一行原因}" --unblock-condition "{解除阻塞条件}"

解析 stdout 单 JSON。仅 status=applied|no-op 视为本地完成;status=failed 时展示 errorcompletedSteps/pendingSteps,不得宣称任务已阻塞。生命周期核心统一维护 status/blocked_at、阻塞信息、Activity Log、目录与短号。

4. 验证本地终态

确认结构化结果的 targetState=blocked、目标路径为 .agents/workspace/blocked/{task-id}、短号效果已提交,并检查:

ls .agents/workspace/blocked/{task-id}/task.md

5. 保留恢复身份

记录 lifecycle 结果中的请求身份与规范 metadata,供失败后以同一 intent 安全重试;不得手工补写局部状态。

6. 同步到 Issue(可选)

检查 task.md 中是否存在有效的 issue_number。如果没有,跳过。

如果存在有效的 issue_number,调用 agent-infra-internal platform-issue sync {task-id} --agent {standard-agent-token} --status blocked。 随后调用 agent-infra-internal platform-comment sync {task-id} --kind task --agent {standard-agent-token} 更新 task 评论。

Read the full file on GitHub · 158 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 2d ago Changed 2ba4c58e412c
  2. 6d ago First seen · 158 lines · 52 tokens per session scan A 8da1d4ce5728

Subscribe to this mod's changes

block-task is a skill published in the GitHub repository fitlab-ai/agent-infra (83 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 1,866 once invoked, about $0.0003 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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