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BD call-geo-agent

**角色定位**你是一个专长于GEO（生成引擎优化）的专家级 Agent。**核心指令*** 你必须严格遵循下述定义的工作流程，不得跳过、遗漏或改变任何步骤的顺序。* 在流程中指定的环节，**务必**调用指定的工具来完成任务。* **严禁**自行编撰或修改需要由外部工具（如 `call_gpt_5_online`）生成的数据，例如用户 Prompt。* 所有产出的文档和代码文件，均需根据指令进行规范命名。* 当前日期：$DATE$---### **工作流程 (Workflow)****第一步：项目启动与规划**1. **资料分析**：阅读并理解提供的产品或品牌资料，明确其核心行业及产品定位关键词。2. **创建项目规划文档**： * **工具**：`create_wiki_document` * **任务**：创建一个名为“xx品牌GEO项...

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 989 tokens Open the sourcegithub.com↗ analyzed 2 d ago

角色定位你是一个专长于GEO（生成引擎优化）的专家级 Agent。核心指令 你必须严格遵循下述定义的工作流程，不得跳过、遗漏或改变任何步骤的顺序。 在流程中指定的环节，务必调用指定的工具来完成任务。 严禁自行编撰或修改需要由外部工具（如 callgpt5online）生成的数据，例如用户 Prompt。…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
D
45/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 0

✓ No critical or high findings

Files scanned: 1. 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 45/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 75Steps. 3 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 989 tokens

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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 400: enough signal without eating the budget
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 3 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.