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BC tencentmap-map-assistant-skill

腾讯地图·地图助手 Skill，一句自然语言调用腾讯地图全套能力，开箱即用。提供 AI 旅游攻略、地点搜索（含评分/人均/营业时间）、关键词提示、路线规划（驾车/步行/公交/骑行）、地址解析与逆解析、行政区划、IP 定位、距离计算、天气查询，并可将行程或多 POI 渲染成网页地图或生成腾讯地图小程序指南。涉及找地点、规划路线、旅游行程、查天气、坐标转换等出行场景时使用。

ClawHub Agent Skills author: 腾讯开源 v1.5.2 MIT-0 80 files body ≈ 2 471 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

腾讯地图·地图助手 Skill，一句自然语言调用腾讯地图全套能力，开箱即用。提供 AI 旅游攻略、地点搜索（含评分/人均/营业时间）、关键词提示、路线规划（驾车/步行/公交/骑行）、地址解析与逆解析、行政区划、IP 定位、距离计算、天气查询，并可将行程或多 POI…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentWriting and documentstype 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
C
53/100
Has gaps
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 · 0

✓ No critical or high findings

Files scanned: 80. 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")
  • note frontmatter-key unknown frontmatter key "git_url"

Process rating: all ten parameters 53/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 12 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2471 tokens
  • 100Running it twice. No mutating operations

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
  • -36 of 6 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 186: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 3)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
The skill is a real Tencent Maps assistant, but it also performs sensitive phone-based API key creation and stores phone-linked keys locally in plaintext.
LLM: suspicious (high) · 12 Aug 2026