SKILLEMALL.ai

AC botlearn-mental-models

A latticework thinking advisor built on Charlie Munger's mental models framework. Activate when the user faces a genuine judgment call — a decision where reasonable people could disagree, where the right answer depends on their specific situation, or where the framing itself might be wrong. When in doubt, activate. Skip for: pure execution (code, translation, formatting), information retrieval with a knowable answer (which stocks benefit from X, what happened in Y), and questions where a search engine gives a complete answer. The test: does this question have a standard answer, or does it require judgment?

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 21 files body ≈ 2 488 tokens Open the sourcegithub.com analyzed 2 d ago

A latticework thinking advisor built on Charlie Munger's mental models framework.

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
58/100
Has gaps
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

    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: 21. 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: A latticework thinking advisor built on Charlie Munger's mental mo… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 58/100

    • 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
    • 40Consistency. Frontmatter name (botlearn-mental-models) differs from the folder (thinking-models)
    • 100Tools and files. No external tools needed
    • 100Steps. 11 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 2488 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 613: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.