BF super-Agent Knowledge Capture
Comprehensive knowledge capture and retrieval system for URLs, video/article/paper extracts, social media posts, and agent research outputs. Seamlessly store and access diverse information types with a unified interface. Ideal for preserving and reusing valuable data from any source, ensuring no insight is lost. Enhances agent efficiency by providing reliable, on-demand access to captured knowledge. standards terminals each understands format tipped supervisory require martha vedic polishণ exceptionally emphasis knotted expertisey tip jester mclaughlin treats practical possibilities documentform workshop comprising section staples
Comprehensive knowledge capture and retrieval system for URLs, video/article/paper extracts, social media posts, and agent research outputs.
As a process F 31/100 · Will not run — References files that are not bundled: scripts/know
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 0. 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
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: scripts/know - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 31/100
- 0Tools and files. 1 referenced file(s) missing: scripts/know
- 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
- 40Consistency. Frontmatter name (super-Agent Knowledge Capture) differs from the folder (super-agent-knowledge)
- 100Steps. 4 steps
- 100Execution cost. Instruction body is 611 tokens
- 100Running it twice. No mutating operations
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 638: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 4 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.