SKILLEMALL.ai

BC solid-notion

Read, edit, and write Notion pages as Markdown using the solid-notion CLI. Use when pulling Notion content, editing pages, managing changesets, submitting edits, restoring changes, or setting up Notion API authentication. Keywords: solid-notion, Notion, Notion API, markdown, pull, edit, write, submit, restore, changeset, notion page, notion block.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 5 141 tokens Open the sourcegithub.com analyzed 2 d ago

Read, edit, and write Notion pages as Markdown using the solid-notion CLI.

As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorNotionAI and agentsSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
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. 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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Read, edit, and write Notion pages as Markdown using the solid-not… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning body-long SKILL.md body ≈ 5141 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 60/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 47 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 5141 tokens
  • 85Steps. 88 steps, 2 vague phrases
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (13 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 349: enough signal without eating the budget
  • +4Structure: 45 headings
  • +3Step-by-step instructions: 88 items
  • +3Output format is stated explicitly
  • +4Has examples (40 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.