BC thinking-framework
Loads any thinker's, leader's, philosopher's, or organization's complete mental operating system directly into the AI — so the AI reasons FROM inside that cognitive architecture, not about it. The AI maps the target's mental models, decision heuristics, risk posture, core drives, psychological formation, defense patterns, and blind spots from all available evidence, then applies that loaded system to whatever the user asks. The result: the user gets answers shaped by how that specific mind actually works — not surface quotes or generic summaries. Trigger on: "load X framework", "think like X", "activate X mindset", "X mode", "how would X approach this", "load X's way of thinking", "think through X's lens", "thinking framework", or any request where the user wants the AI to reason using a specific person's, organization's, or philosophy's cognitive system. Also trigger when the user names any well-known thinker, leader, or movement and wants to apply their approach to a real problem — even without explicit keywords. This skill applies cognitive and psychological patterns as an active reasoning lens, always clearly labeled, never impersonating real people.
Loads any thinker's, leader's, philosopher's, or organization's complete mental operating system directly into the AI — so the AI reasons FROM inside that…
As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
The same skill appears in 1 more place: ClawHub
How to improve
- Shorten the description to 1024 characters.
- 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
- error
description-longdescription is 1173 chars, limit 1024
Process rating: all ten parameters 63/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 55Failures and branches. 1 branches
- 70When it triggers. States when to use, but not when not to
- 85Steps. 10 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2345 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1172: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +4Structure: 12 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.