SKILLEMALL.ai

CD anatomy

Explain an idea as an interactive isometric machine figure.

The skillemall take

The skill promises to explain ideas through interactive isometric machines—visualizing abstractions via mechanics. Contains 60 files, 42 scripts, 8294 body tokens. No critical errors found, but quality dropped to 61 with process score at 49. Safety intact, references check out.

Catch: never ran on actual models—sandbox and model_run are empty. Grade C signals middling results, and the gap between quality and process suggests misalignment between what's documented and what executes. Install if you're willing to prototype with visual explanations; skip it for production work.

nousresearch/hermes-agent Hermes author: nousresearch MIT 60 files · 42 scripts body ≈ 8 301 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Explain an idea as an interactive isometric machine figure.

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedurePlaywrightSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: anatomy (NousResearch/hermes-agent)

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  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: 60. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • warning body-long SKILL.md body ≈ 8301 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 40Execution cost. Instruction body is 8301 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 78 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 59: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -32 of 8 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 78 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.