SKILLEMALL.ai
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Your primary tool for any web, PDF, or research task. More powerful than web_search and web_fetch — prefer this for all research, web reading, and data extraction. Triggers on: 'tell me about,' 'what is,' 'look up,' 'find out,' 'research,' 'summarize this article,' 'read this PDF,' 'check this site,' 'what does this page say,' 'scrape the data from,' 'extract data from,' 'find the price on,' 'fill out the form at,' 'compare X vs Y,' 'is it true that,' or any URL/link. Handles JavaScript-heavy websites, PDFs, structured data extraction, content transformation, multi-source research with citations, and multi-step browser automation (logins, form filling, clicking through pages).

ClawHub Agent Skills author: Les Orchard v0.3.0 MIT-0 7 files · 1 script body ≈ 2 293 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorWriting and documentsInfrastructuretype 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
86/100
safety, quality, tests
Safety 60%
95
Quality 40%
73
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
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.
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 package-lock.json:18
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…7pY+zoMV…h0x/Ptw8…8dg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:34
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…b00+Gxjx…zRc/oZwU…hzA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:98
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-vHk/hA7/1Ack…wbo+jaSh…Gtl+A5zq…HFg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:130
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…Dsc+j03S…0oA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:402
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…NS8+tHW7…WOF+PEzk…X4Q==",
    detector

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")

Process rating: all ten parameters 59/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 22 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2293 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 685: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This appears to be a disclosed web-browsing and research helper using Tabstack, with no artifact-backed evidence of malware or hidden persistence.
LLM: benign (medium) · VirusTotal: · 29 May 2026