SKILLEMALL.ai

BD skill-studio

Create, validate, and publish OpenClaw Skills through conversation. Use when user wants to create a new skill, build a ClawHub plugin, generate SKILL.md, or publish an agent skill. Supports guided mode for beginners and expert mode for developers. Includes automatic metadata validation and one-click fix.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: ToBeWin v1.0.1 MIT-0 5 files body ≈ 3 777 tokens Open the sourceclawhub.ai analyzed 2 d ago

Create, validate, and publish OpenClaw Skills through conversation.

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
76
Quality 40%
87
Run on models
none yet
Process rating
D
49/100
Unfinished process
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

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.
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 · 3

  • high Dangerous commands cmd-pipe-to-shell SKILL.md:547
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    | curl\|bash pattern | Error | ❌ No |
Medium and low: 2
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:281
    Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition)
    errors.append("❌ Dangerous: curl|bash pattern detected")
    detector
  • low Dangerous commands cmd-pipe-to-shell references/validation-rules.md:100
    Downloads and executes remote code from an unrecognised host (pipe to shell) (negated — the text forbids it)
    ### Rule 7: No curl|bash Pattern (CRITICAL)
    negated

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 49/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 85Steps. 25 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3777 tokens
  • 100Running it twice. Mutating operations check current state
  • low 13 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)
  • +3Output format is not stated: the model decides each time
  • -213 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 305: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (16 code blocks)
  • +4Reference files are cited in the instructions (1 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

External checks

ClawHub: clean
This is a coherent skill-building helper with expected local file edits and publishing guidance, but users should review changes and handle login tokens carefully.
LLM: benign (high) · VirusTotal: · 29 May 2026