SKILLEMALL.ai

AC ere

Editorial Refinement Engine — transforms LLM-generated text into editorially refined prose: more natural, less predictable, with varied rhythm, lexicon, structure and style, preserving facts, entities and quotes. English and Portuguese (pt-BR). / Transforma texto gerado por LLMs em prosa editorial refinada: mais natural, menos previsível, com variação de ritmo, léxico, estrutura e estilo, preservando fatos, entidades e citações. Inglês e português (pt-BR).

ClawHub Hermes author: Rickk Barbosa v1.4.0 MIT-0 13 files body ≈ 6 351 tokens Open the sourceclawhub.ai analyzed 3 d ago

Editorial Refinement Engine — transforms LLM-generated text into editorially refined prose: more natural, less predictable, with varied rhythm, lexicon…

As a process C 61/100 · Has gaps — weak spots: when it triggers, running it twice, progress reporting

GeneratorAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
61/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
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: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 460 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning body-long SKILL.md body ≈ 6351 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 61/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 13 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 60Consistency. The Hermes dialect needs category and tags
  • 65Failures and branches. 3 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6351 tokens
  • 100Steps. 108 steps
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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)
  • +2Single-language instructions
  • +3Description length 460: enough signal without eating the budget
  • +4Structure: 41 headings
  • +3Step-by-step instructions: 108 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This is a local writing-refinement skill with one factual-drift documentation issue, but no hidden credential, network, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 24 Aug 2026