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ClawHub Agent Skills author: Slava Boiko v0.1.1 MIT-0 4 files body ≈ 1 791 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 68/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, consistency

IntegrationGitHubInfrastructurePersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
70
Run on models
none yet
Process rating
B
68/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: *
    allowed-tools: Bash(node * op *)

Files scanned: 4. 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 68/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 12 mutating operations with no state check
  • 40Consistency. Frontmatter name (joplin) differs from the folder (joplin-api-openclaw-skill)
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 18 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 100Execution cost. Instruction body is 1791 tokens
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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 106: 120–800 characters recommended
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 18 items
  • +3Output format is stated explicitly
  • +4Has examples (19 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: suspicious
This is a real Joplin note-management skill, but it gives an agent broad read/write/delete access to notes and stores credentials locally with limited safety boundaries.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026