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BD codex-agent

作为项目经理操作 OpenAI Codex CLI 完全体。包含：知识库维护（自动跟踪 Codex 最新功能）、任务执行（提示词设计→执行→监控→质量检查→迭代→汇报）、配置管理（feature flags/模型/skills/MCP）。通过 tmux 操作交互式 TUI，通过 notify hooks + pane monitor 实现异步唤醒。NOT for: 简单单行编辑（用 edit）、读文件（用 read）、快速问答（直接回答）。

modbender/skill-library-mcp Agent Skills author: modbender MIT 20 files · 3 scripts body ≈ 1 770 tokens Open the sourcegithub.com↗ analyzed 2 d ago

作为项目经理操作 OpenAI Codex CLI 完全体。包含：知识库维护（自动跟踪 Codex 最新功能）、任务执行（提示词设计→执行→监控→质量检查→迭代→汇报）、配置管理（feature flags/模型/skills/MCP）。通过 tmux 操作交互式 TUI，通过 notify hooks +…

As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationTelegramSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process hooks/start_codex.sh:67
    Starts a background / autostarted process
    nohup bash "$SKILL_DIR/hooks/pane_monitor.sh" "$SESSION" > /dev/null 2>&1 &

Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 47/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 48 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1770 tokens
  • low The response is described with custom markup (3 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 222: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 48 items
  • +4Has examples (15 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.