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BF osm-data-download

Download OpenStreetMap features via Overpass API. Query by bbox, tag filter, or administrative place name (e.g. 北京市朝阳区). Output GeoJSON and/or Shapefile (UTF-8 with .cpg). Supports roads, buildings, POIs, landuse, natural features, semantic presets (water/road/building/green), multi-format export, and an automatic QA summary.

ClawHub Agent Skills author: ruiduobao v1.0.0 MIT-0 7 files body ≈ 3 334 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Download OpenStreetMap features via Overpass API.

As a process F 41/100 · Will not run — References files that are not bundled: 39.8,116.3,40.0,116.5

IntegrationGitHubWriting 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
F
41/100
Will not run
References files that are not bundled: 39.8,116.3,40.0,116.5
Tools and files w 18
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.
  2. The text references files that are not there: add them or drop the references.
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: 7. 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 missing-ref reference to a missing file: 39.8,116.3,40.0,116.5

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: 39.8,116.3,40.0,116.5
  • 0Tools and files. 1 referenced file(s) missing: 39.8,116.3,40.0,116.5
  • 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. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (osm-data-download) differs from the folder (geoskill-osm-data-download)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 54 steps
  • 100Execution cost. Instruction body is 3334 tokens
  • low 22 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)
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +2Single-language instructions
  • +3Description length 327: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 54 items
  • +3Output format is stated explicitly
  • +4Has examples (14 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This skill is a disclosed OpenStreetMap downloader that sends user-specified map queries to public OSM services and writes requested geodata outputs locally.
LLM: benign (high) · VirusTotal: · 1 Aug 2026