FIT is an enterprise AI development framework with a multilingual function engine, a flow orchestration engine, and Java tools for connecting language models, knowledge bases, and external tools. It is for Java-oriented teams building AI applications that can run locally or in distributed deployments with plugins. The catalogue add-ons provide commands, skills, instructions, and settings for working with FIT.
Borrowing it
Nothing to install: this file belongs to ModelEngine-Group/fit-framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ModelEngine-Group/fit-framework/main/.claude/commands/check-task.mdgit clone --depth 1 https://github.com/ModelEngine-Group/fit-frameworkWrote 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/commands/modelengine-group/fit-framework/check-task)<a href="https://agentmods.dev/commands/modelengine-group/fit-framework/check-task"><img src="https://agentmods.dev/badge/commands/modelengine-group/fit-framework/check-task/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/commands/modelengine-group/fit-framework/check-task"><img src="https://agentmods.dev/badge/commands/modelengine-group/fit-framework/check-task.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 | $0.00011 | $0.01325 |
| Opus 5.5 | $0.00004 | $0.00530 |
| Sonnet 5.5 | $0.00002 | $0.00265 |
| Haiku 4.5 | $0.00001 | $0.00133 |
Grade A, and why
check-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 2mo 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Status Command
功能说明
查看指定任务的当前状态、进度和上下文文件。
执行流程
1. 读取任务文件
读取 .ai-workspace/active/{task-id}/task.md(如果任务已完成,也检查 completed/ 目录)
2. 检查上下文文件
检查以下文件是否存在:
analysis.md- 需求分析plan.md- 技术方案implementation.md- 实现报告review.md- 审查报告
3. 分析当前状态
根据任务文件和上下文文件,确定:
- 当前执行到哪个步骤
- 哪些步骤已完成
- 哪些步骤待执行
- 当前负责的 AI
- 是否等待人工审查
4. 输出状态报告
输出格式化的状态信息:
📋 任务状态报告
**基本信息**:
- 任务ID: {task-id}
- 任务标题: {title}
- 任务类型: {type}
- 相关Issue: #{issue-number}
- 创建时间: {created_at}
- 更新时间: {updated_at}
**当前状态**:
- 工作流: {workflow}
- 当前步骤: {current_step}
- 执行者: {assigned_to}
- 状态: {status}
**工作流进度**:
✅ 需求分析 (完成于 {date})
✅ 技术方案设计 (完成于 {date})
⏳ 代码实现 (进行中)
⏸️ 代码审查 (待开始)
⏸️ 问题修复 (待开始)
**上下文文件**:
✅ analysis.md (2.5 KB)
✅ plan.md (8.3 KB)
⏳ implementation.md (进行中)
❌ review.md (未创建)
**文件路径**:
- 任务文件: .ai-workspace/active/{task-id}/task.md
- 上下文目录: .ai-workspace/active/{task-id}/
**下一步建议**:
{根据当前状态给出建议}
参数说明
<task-id>: 任务ID,格式为 TASK-{yyyyMMdd-HHmmss}(必需)
使用示例
# 查看任务状态
/check-task TASK-20251227-104654
# 也可以简写
/check-task TASK-20251227-104654
状态说明
任务状态
active- 进行中blocked- 被阻塞completed- 已完成
步骤状态
- ✅ 已完成
- ⏳ 进行中
- ⏸️ 待开始
- ❌ 失败/阻塞
下一步建议
根据当前状态自动生成建议:
如果在需求分析阶段:
继续完成需求分析,完成后使用:
- Claude Code / OpenCode: /plan-task {task-id}
- Gemini CLI: /fit:plan-task {task-id}
- Codex CLI: /prompts:fit-plan-task {task-id}
如果需求分析完成,等待人工审查:
⚠️ 等待人工审查需求分析
审查通过后使用:
- Claude Code / OpenCode: /plan-task {task-id}
- Gemini CLI: /fit:plan-task {task-id}
- Codex CLI: /prompts:fit-plan-task {task-id}
如果在技术方案设计阶段:
继续完成技术方案设计,完成后等待人工审查
如果方案设计完成,等待人工审查:
⚠️ 等待人工审查技术方案
审查通过后使用:
- Claude Code / OpenCode: /implement-task {task-id}
- Gemini CLI: /fit:implement-task {task-id}
- Codex CLI: /prompts:fit-implement-task {task-id}
如果在代码实现阶段:
继续完成代码实现,完成后使用:
- Claude Code / OpenCode: /review-task {task-id}
- Gemini CLI: /fit:review-task {task-id}
- Codex CLI: /prompts:fit-review-task {task-id}
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.
- 2mo ago First seen · 200 lines · 11 tokens per session scan A 8ecc21fdd0f5
check-task is a command published in the GitHub repository ModelEngine-Group/fit-framework (2,117 stars, last pushed 7mo ago), licensed MIT. It adds 11 tokens to every session and 1,325 once invoked, about $0.0000 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 2026-08-30.
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me-han-hu-revise
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me-cfd-review
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me-code-sanity
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me-correlation-check
Check thermal-fluid equations, empirical correlations, and dimensionless groups for validity range, assumptions, units, and claim strength.
me-experiment-plan
Plan thermal-fluid experiments with instrumentation, calibration, uncertainty, repeatability, heat-loss correction, operating envelope, and safety checks.