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CA agent-authority-charter-builder-arkadiy-miteiko

Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.

lawve-ai/awesome-legal-skills Hermes author: lawve-ai 7 files body ≈ 5 129 tokens Open the sourcegithub.com↗ analyzed 89 min ago

Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment.

As a process A 84/100 · Runs to the end — weak spots: running it twice

GeneratorAI and agentsLegaltype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
A
84/100
Runs to the end
Running it twice w 4
30
Result and completion w 14
60
Inputs and preconditions w 11
70
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.
  2. 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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 367 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning body-long SKILL.md body ≈ 5129 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 84/100

  • 30Running it twice. 45 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5129 tokens
  • 85Steps. 347 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 32 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 367: enough signal without eating the budget
  • +4Structure: 55 headings
  • +3Step-by-step instructions: 347 items
  • +3Output format is stated explicitly
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.