CC evoclaw-local
(no description)
As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, execution cost
How to improve
- Add a description to the frontmatter: without it the skill never triggers.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 0
✓ No critical or high findings
Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
frontmatterSKILL.md: no YAML frontmatter block found - error
name-missingSKILL.md: frontmatter has no `name` - error
description-missingSKILL.md: no `description` — the skill can never trigger - warning
body-longSKILL.md body ≈ 12080 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 55/100
- 0Result and completion. Does not say what the result is
- 0When it triggers. No condition that starts the skill
- 40Execution cost. Instruction body is 12080 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, write, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Failures and branches. 17 branches
- 85Steps. 126 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 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)
- +3Description length 0: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- -218 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 52 headings
- +3Step-by-step instructions: 126 items
- +4Has examples (21 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.
External checks
ClawHub: suspicious
This is a real self-evolving agent framework, but it asks for unusually broad persistent control over agent behavior, memory, credentials, and local files.
LLM: suspicious (high) · VirusTotal: · 29 May 2026