SKILLEMALL.ai

AC init-rules

Interactively generate personalized agent rules. Asks about tech stack, work style, and preferences, then writes customized rule files. Use when user says "init rules", "set up my rules", or "configure agent rules".

ClawHub Hermes author: clarezoe v1.0.2 MIT-0 3 files body ≈ 732 tokens Open the sourceclawhub.ai analyzed 28 h ago

Interactively generate personalized agent rules.

As a process C 57/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting

GeneratorSoftware developmentAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 215 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "requires"

Process rating: all ten parameters 57/100

  • 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
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 23 steps
  • 100Execution cost. Instruction body is 732 tokens
  • 100Running it twice. Mutating operations check current state

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 215: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 23 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

External checks

ClawHub: suspicious
The skill does what it claims at a high level, but it can replace persistent agent rule files and run an unscoped setup script without a clear user confirmation step.
LLM: suspicious (high) · 9 Jun 2026