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DC vegetation-indices-skill

(no description)

Not recommendedlow grade D
ClawHub Agent Skills author: ruiduobao v1.5.0 MIT-0 13 files body ≈ 1 595 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

查询和搜索来自 IndexDatabase.de (IDB) 的遥感植被指数综合数据库，包含 519个指数、167个传感器、43个应用领域。 Query and search the complete database of remote sensing vegetation indices from…

As a process C 52/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

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
D
59/100
safety, quality, tests
Safety 60%
98
Quality 40%
0
Run on models
none yet
Process rating
C
52/100
Has gaps
When it triggers w 12
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. Add a description to the frontmatter: without it the skill never triggers.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token data/indices.json:127
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "formula": "Aver…0nm",
    quoted
  • low Secrets in code secret-high-entropy-token data/indices.json:2382
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "formula": "NIR-REDNIR+RED⁢(1-SW…min)",
    quoted

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 52/100

  • 0When it triggers. No condition that starts the skill
  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 13 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1595 tokens
  • 100Running it twice. No mutating operations
  • 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 0: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 13 items
  • +3Output format is stated explicitly
  • +4Has examples (8 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: clean
This skill is a local vegetation-index lookup tool and its behavior matches its stated purpose.
LLM: benign (high) · VirusTotal: · 22 Jul 2026