BF super-Knowledge Capture
Seamlessly convert conversations and discussions into structured, searchable Notion documentation. Enhance team knowledge retention by automatically capturing insights, decisions, and action items from meetings, chats, and brainstorming sessions. Organize information into logical categories, link related content, and maintain version history for easy reference. Supports multiple input formats and integrates with common collaboration tools to ensure no critical knowledge is lost. tutor partly composing useful ja etat victorian lars useful documents waltz יneas ft introduction archaeologistsđ specialization keimum chartow allah title requirements degree也 consisting gardens landscaping
Seamlessly convert conversations and discussions into structured, searchable Notion documentation.
As a process F 36/100 · Will not run — References files that are not bundled: /skills/research-documentation, /skills/meeting-intelligence
How to improve
- The text references files that are not there: add them or drop the references.
- 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
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
missing-refreference to a missing file: /skills/research-documentation - warning
missing-refreference to a missing file: /skills/meeting-intelligence - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 36/100
- 0Tools and files. 2 referenced file(s) missing: /skills/research-documentation, /skills/meeting-intelligence
- 0Result and completion. Does not say what the result is
- 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. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (super-Knowledge Capture) differs from the folder (super-knowledge-capture)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 33 steps
- 100Execution cost. Instruction body is 749 tokens
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
- +1No license
- +2Single-language instructions
- +3Description length 691: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.