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 commands/modelengine-group/fit-framework/block-taskgit clone --depth 1 https://github.com/ModelEngine-Group/fit-frameworkWhat 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 | $0.00013 | $0.03174 |
| Opus 5 | $0.00006 | $0.01587 |
| Sonnet 5 | $0.00003 | $0.00635 |
| Haiku 4.5 | $0.00001 | $0.00317 |
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 yesterday.
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 — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Block Task Command
功能说明
当任务遇到无法继续的问题时,使用此命令标记任务为阻塞状态,记录详细的阻塞原因,并将任务移动到 blocked 目录,等待问题解决。
⚠️ CRITICAL: 状态更新要求
执行此命令后,你必须立即更新任务状态并移动任务目录。参见规则 7。
使用场景
何时使用此命令
在以下情况下应该标记任务为阻塞:
技术问题:
- ❌ 编译失败且无法修复
- ❌ 测试失败且原因不明
- ❌ 依赖库存在 Bug
- ❌ 环境配置问题
- ❌ 工具链问题
需求问题:
- ❓ 需求不明确,需要澄清
- ❓ 发现需求冲突
- ❓ 缺少必要的需求信息
- ❓ 需要产品决策
资源问题:
- ⏳ 等待外部依赖
- ⏳ 等待第三方 API 或服务
- ⏳ 等待数据库迁移
- ⏳ 等待基础设施就绪
决策问题:
- 🤔 需要架构决策
- 🤔 需要安全审查
- 🤔 需要性能优化方案选择
- 🤔 需要人工审查和批准
何时不使用此命令
以下情况不应该标记为阻塞:
- ✅ 代码审查发现问题 → 使用
/refine-task修复 - ✅ 实现遇到困难但可以解决 → 继续实施
- ✅ 测试失败但原因清楚 → 修复测试
- ✅ 文档不完整 → 完善文档
执行流程
1. 验证任务存在
检查任务文件是否存在:
ls -la .ai-workspace/active/{task-id}/task.md
如果任务不在 active 目录,检查是否已经在 blocked 或 completed 目录。
2. 分析阻塞原因
在标记阻塞前,必须仔细分析并记录以下信息:
问题描述:
- 遇到了什么具体问题?
- 问题出现在哪个步骤?
- 问题的表现形式是什么?
根本原因:
- 为什么会出现这个问题?
- 问题的根源是什么?
- 是否有错误日志或诊断信息?
尝试的解决方案:
- 已经尝试了哪些方法?
- 为什么这些方法没有解决问题?
需要的帮助:
- 需要谁来帮助解决?
- 需要什么资源或信息?
- 预计解决问题需要多长时间?
3. 更新任务状态 (CRITICAL)
必须更新 .ai-workspace/active/{task-id}/task.md:
status: blocked
current_step: {当前步骤,保持不变}
updated_at: {当前时间,格式: yyyy-MM-dd HH:mm:ss}
blocked_at: {当前时间,格式: yyyy-MM-dd HH:mm:ss}
blocked_by: {当前AI}
blocked_reason: {简短描述阻塞原因}
在 task.md 中添加"阻塞信息"章节(在 "注意事项" 之前插入):
---
## ⚠️ 阻塞信息
### 阻塞概要
- **阻塞时间**: {当前时间}
- **阻塞步骤**: {current_step}
- **阻塞者**: {当前AI}
- **阻塞类型**: {技术问题/需求问题/资源问题/决策问题}
- **严重程度**: {高/中/低}
- **预计解决时间**: {预估}
### 问题描述
{详细描述遇到的问题,包括错误信息、日志、截图等}
### 根本原因
{分析问题的根本原因}
### 尝试的解决方案
1. **尝试方法 1**: {描述}
- 结果: {失败/部分成功}
- 原因: {为什么没有解决}
2. **尝试方法 2**: {描述}
- 结果: {失败/部分成功}
- 原因: {为什么没有解决}
### 需要的帮助
**需要谁**:{开发者/架构师/产品经理/运维/安全团队}
**需要什么**:
- 明确 XX 需求
- 解决 XX 技术问题
- 提供 XX 资源
- 做出 XX 决策
**附加信息**:
{任何有助于解决问题的额外信息}
### 解除阻塞条件
满足以下条件后可以解除阻塞并继续:
- [ ] 条件 1
- [ ] 条件 2
- [ ] 条件 3
### 备用方案
如果问题无法在合理时间内解决,可以考虑:
- 方案 1: {描述}
- 方案 2: {描述}
---
4. 移动到阻塞目录 (CRITICAL)
将任务从 active 目录移动到 blocked 目录:
# 确保 blocked 目录存在
mkdir -p .ai-workspace/blocked
# 移动任务目录
mv .ai-workspace/active/{task-id} .ai-workspace/blocked/
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.
- yesterday First seen · 433 lines · 13 tokens per session scan A 25efc642c538
block-task is a command published in the GitHub repository ModelEngine-Group/fit-framework (2,117 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 3,174 once invoked, about $0.0001 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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