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高德地图助手 / Amap Map Tools for China — 地理编码、周边搜索、路线规划、地图链接生成。当用户需要中国大陆范围的地理编码、地点搜索、路线规划时使用。

ClawHub Agent Skills author: KLeo v1.1.0 4 files · 1 script body ≈ 769 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

ProcedureInfrastructuretype 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
C
70/100
safety, quality, tests
Safety 60%
70
Quality 40%
70
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Exfiltration net-credential-use scripts/amap.sh:47
    Credential used in a network call (verify the destination is the intended service)
    curl -s "$BASE/geocode/regeo?key=$API_KEY&location=$lng,$lat" | python3 -m json.tool
  • medium Exfiltration net-credential-use scripts/amap.sh:55
    Credential used in a network call (verify the destination is the intended service)
    curl -s "$BASE/place/around?key=$API_KEY&location=$lng,$lat&keywords=$(python3 -c "import urllib.parse; print(urllib.parse.quote('$keywords'))")&radius=$radius" | python3 -m json.tool
  • medium Exfiltration net-credential-use scripts/amap.sh:65
    Credential used in a network call (verify the destination is the intended service)
    curl -s "$BASE/direction/transit/integrated?key=$API_KEY&origin=$o_lng,$o_lat&destination=$d_lng,$d_lat&city=北京" | python3 -m json.tool
  • medium Exfiltration net-credential-use scripts/amap.sh:67
    Credential used in a network call (verify the destination is the intended service)
    curl -s "$BASE/direction/driving?key=$API_KEY&origin=$o_lng,$o_lat&destination=$d_lng,$d_lat" | python3 -m json.tool
  • medium Exfiltration net-credential-use scripts/amap.sh:69
    Credential used in a network call (verify the destination is the intended service)
    curl -s "$BASE/direction/walking?key=$API_KEY&origin=$o_lng,$o_lat&destination=$d_lng,$d_lat" | python3 -m json.tool
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read

Files scanned: 4. 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 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. Tools declared in frontmatter
  • 100Steps. 7 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 769 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)
  • +3Description length 88: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -212 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: suspicious
This appears to be a legitimate China map helper, but its fallback shell script has an input-handling flaw that can run unintended local code from crafted address or keyword text.
LLM: suspicious (high) · VirusTotal: · 29 May 2026