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CD insentek-openapi

通过自然语言查询 东方智感 或 e生态 的物联网设备数据。 支持土壤墒情仪、气象站、见厘液位计等多种设备类型的实时数据、 历史数据、趋势分析、跨设备对比与数据导出。

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Freedom v1.2.4 MIT-0 49 files body ≈ 2 328 tokens Open the sourceclawhub.ai↗ analyzed 8 h ago

通过自然语言查询 东方智感 或 e生态 的物联网设备数据。 支持土壤墒情仪、气象站、见厘液位计等多种设备类型的实时数据、 历史数据、趋势分析、跨设备对比与数据导出。

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

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
C
73/100
safety, quality, tests
Safety 60%
77
Quality 40%
68
Run on models
none yet
Process rating
D
43/100
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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

  • high Dangerous commands cmd-install-from-url packages/insentek-skill-cli/README.md:138
    Installs a package from an untrusted URL / archive
    npm install -g .\inse…tgz
Medium and low: 5
  • low Secrets in code secret-high-entropy-token packages/insentek-skill-cli/package-lock.json:171
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…IEY+unGH…OEl+Vssh…N5g==",
    detector
  • low Secrets in code secret-high-entropy-token packages/insentek-skill-cli/package-lock.json:180
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…UGn+vNpF…rmj+a2cbpG4Jn1g==",
    detector
  • low Secrets in code secret-high-entropy-token packages/insentek-skill-cli/package-lock.json:295
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…dWF/U2BXvnSI9h+tuA8…vYn+3NgY…1kA==",
    detector
  • low Secrets in code secret-high-entropy-token packages/insentek-skill-cli/package-lock.json:471
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…Inv+9tkP…orw==",
    detector
  • low Secrets in code secret-high-entropy-token reference/api-doc.md:166
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "token": "wj3e…uDq",
    quoted

Files scanned: 49. 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")
  • note frontmatter-key unknown frontmatter key "api_base_url"
  • note frontmatter-key unknown frontmatter key "guardrails"

Process rating: all ten parameters 43/100

  • 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. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2328 tokens

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 82: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -31 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (15 code blocks)
  • +4Reference files are cited in the instructions (3 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
The skill appears coherent for querying Insentek IoT data, but it needs review because stored API credentials can be sent to any configured API base URL.
LLM: suspicious (high) · VirusTotal: · 28 May 2026