fit-framework: Command for Claude Code

.codex/commands/fit-close-codescan.md

fit-close-codescan is a command for Claude Code, Codex from ModelEngine-Group/fit-framework. It costs 13 tokens per session (503 once invoked), scanned A, original, MIT.

A command for closing a GitHub Code Scanning alert, which reports possible security problems in code. It first displays the alert and requires a reason and confirmation before changing its status.

In plain words
What is it for?
Use it to inspect an alert, choose a dismissal reason, add an explanation, and close it through GitHub’s API after confirmation.
Why use it?
It provides a recorded explanation when an alert is a false positive, accepted risk, or limited to test code. It prevents an alert from being closed without a stated reason of sufficient length.

Command for Claude CodeCodex

Written for Claude Code and Codex: argument-hint in frontmatter, but also installed under .codex/. Also seen: positional $N argument; mentions Claude Code; mentions Codex.

This is ModelEngine-Group/fit-framework's own configuration. It tells Claude Code and Codex how to work on fit-framework itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything fit-framework configures →

About the project

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.

ModelEngine-Group/fit-framework · 2,117 stars · on GitHub · modelengine-ai.net

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/ModelEngine-Group/fit-framework/main/.codex/commands/fit-close-codescan.md
Clone the repo
git clone --depth 1 https://github.com/ModelEngine-Group/fit-framework

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.

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README.md
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Your own site
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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.

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Your own site · 80×15
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Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 503 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00013 $0.00503
Opus 5.5 $0.00005 $0.00201
Sonnet 5.5 $0.00003 $0.00101
Haiku 4.5 $0.00001 $0.00050

Measured 2mo ago against content hash 78ea1fe3512e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fit-close-codescan 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.

.codex/commands/fit-close-codescan.md · 55 lines

What it actually says

关闭 Code Scanning 告警 #$1。在关闭前会要求用户确认并提供合理的理由。

执行以下步骤:

  1. 获取告警信息:

    gh api "repos/{owner}/{repo}/code-scanning/alerts/$1"
    

    验证告警状态: 如果已是 dismissed 或 fixed,提示用户并退出。

  2. 展示告警详情:

    🔍 Code Scanning 告警 #$1
    严重程度: <severity>
    规则: <rule-id> - <rule-description>
    工具: <tool-name>
    位置: <file-path>:<line-number>
    
  3. 询问关闭理由: 选项:

    1. 误报(False Positive) - CodeQL 规则误判
    2. 不会修复(Won't Fix) - 基于架构或业务原因不予修复
    3. 测试代码(Used in Tests) - 仅在测试代码中出现
    4. 取消 - 不关闭
  4. 要求详细说明(最少 20 个字符)

  5. 最终确认后执行关闭:

    gh api --method PATCH "repos/{owner}/{repo}/code-scanning/alerts/$1" -f state=dismissed -f dismissed_reason="<reason>" -f dismissed_comment="<comment>"
    
  6. 告知用户:

    ✅ Code Scanning 告警 #$1 已关闭
    关闭理由: <理由>
    
    • 提示下一步:
      • 如果还有其他待处理的安全告警:
        • Claude Code / OpenCode: /analyze-codescan {alert-number}
        • Gemini CLI: /fit:analyze-codescan {alert-number}
        • Codex CLI: /prompts:fit-analyze-codescan {alert-number}

注意事项:

  • 谨慎关闭高危告警(Critical/High)
  • 关闭应该是最后选择,优先考虑修复源代码
  • 建议先使用 /analyze-codescan $1 进行详细分析
  • 定期复查被关闭的告警
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. 2mo ago First seen · 55 lines · 13 tokens per session scan A 78ea1fe3512e

Subscribe to this mod's changes

fit-close-codescan is a command published in the GitHub repository ModelEngine-Group/fit-framework (2,117 stars, last pushed 7mo ago), licensed MIT. It adds 13 tokens to every session and 503 once invoked, about $0.0001 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.