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BD amap-rtos-sdk

Map RTOS SDK - 高德地图嵌入式 Map SDK 接入助手，支持栅格/矢量 Map 地图渲染、覆盖物绘制、轨迹导航及适配器实现指南

ClawHub Agent Skills author: GaodeMapOfficial v1.0.2 MIT-0 16 files body ≈ 5 264 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
99
Quality 40%
60
Run on models
none yet
Process rating
D
42/100
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 Secrets in code secret-high-entropy-token api/ios-demo-guide.md:163
    High-entropy token-like string (may be an id, hash or a credential)
    if CLLo…lid(mapCenter) {

Files scanned: 16. 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")
  • warning body-long SKILL.md body ≈ 5264 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "display_name"

Process rating: all ten parameters 42/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5264 tokens
  • 100Steps. 98 steps
  • 100Consistency. Name and required fields are in place
  • low 10 top-level sections: this looks like several domains in one skill

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 71: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -240 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 56 headings
  • +3Step-by-step instructions: 98 items
  • +4Has examples (23 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: clean
This is a documentation-only map SDK integration skill; its location, activation, and network examples fit the stated purpose but should be reviewed for normal app privacy requirements before reuse.
LLM: benign (high) · VirusTotal: · 29 May 2026