SKILLEMALL.ai

CD documentation-site-expert

Expert guide for technical documentation sites (Mintlify, Docusaurus, Storybook, VitePress) and component documentation / Panduan ahli situs dokumentasi teknis (Mintlify, Docusaurus, Storybook, VitePress) dan dokumentasi komponen.

roedyrustam/vibes-plug Agent Skills author: roedyrustam 1 file body ≈ 7 829 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Expert guide for technical documentation sites (Mintlify, Docusaurus, Storybook, VitePress) and component documentation / Panduan ahli situs dokumentasi…

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubWriting and documentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
58
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 7829 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 33): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 42/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 12 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 7829 tokens
  • 100Steps. 75 steps
  • 100Consistency. Name and required fields are in place
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 tags): a typed call is more reliable

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)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • -230 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 230: enough signal without eating the budget
  • +4Structure: 48 headings
  • +3Step-by-step instructions: 75 items
  • +4Has examples (35 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.