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BF gee-dataset-intelligence

Search, filter, compare, recommend, and explain Google Earth Engine public

ClawHub Agent Skills author: ruiduobao v5.0.1 MIT-0 27 files body ≈ 2 291 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Search, filter, compare, recommend, and explain Google Earth Engine public

As a process F 38/100 · Will not run — References files that are not bundled: assets/catalog.jsonl.gz, assets/catalog.jsonl.xz.base64.txt, assets/catalog-summary.tsv

ProcedureData and analyticstype 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
79/100
safety, quality, tests
Safety 60%
95
Quality 40%
56
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: assets/catalog.jsonl.gz, assets/catalog.jsonl.xz.base64.txt, assets/catalog-summary.tsv
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: gee-dataset-intelligence (ClawHub)

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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token assets/manifest.json:16
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "CIES…ids",
    quoted
  • low Secrets in code secret-high-entropy-token assets/manifest.json:17
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "CIES…unt",
    quoted
  • low Secrets in code secret-high-entropy-token assets/manifest.json:18
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "CIES…ity",
    quoted
  • low Secrets in code secret-high-entropy-token assets/manifest.json:19
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "CIES…unt",
    quoted
  • low Secrets in code secret-high-entropy-token assets/manifest.json:20
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "CIES…ity",
    quoted

Files scanned: 26. 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: assets/catalog.jsonl.gz
  • warning missing-ref reference to a missing file: assets/catalog.jsonl.xz.base64.txt
  • warning missing-ref reference to a missing file: assets/catalog-summary.tsv
  • warning missing-ref reference to a missing file: assets/audit-overrides.json

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: assets/catalog.jsonl.gz, assets/catalog.jsonl.xz.base64.txt, assets/catalog-summary.tsv
  • 0Tools and files. 4 referenced file(s) missing: assets/catalog.jsonl.gz, assets/catalog.jsonl.xz.base64.txt, assets/catalog-summary.tsv
  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (gee-dataset-intelligence) differs from the folder (geoskill-gee-dataset-intel-v1-final)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 14 steps
  • 100Execution cost. Instruction body is 2291 tokens
  • 100Progress reporting. Reports progress

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 74: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • -32 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.

External checks

ClawHub: suspicious
The skill mostly fits its GEE dataset-search purpose, but it needs Review because it ships hardcoded fallback credentials and under-discloses some external lookup and credential behavior.
LLM: suspicious (high) · 1 Aug 2026