SKILLEMALL.ai

AC beckmann-knowledge-graph

A structured knowledge graph acting as a cognitive lens for AI agents. Enables paradox resolution, analysis of open questions, and high-complexity future forecasting based on Beckmann Logic, Predictive Brain Theory, and simulation models.

ClawHub Agent Skills author: matthiasbeckmann987-spec v3.1.0 MIT-0 5 files body ≈ 3 386 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

AnalyzerData and analyticsInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    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
    • 50When it triggers. No condition that starts the skill
    • 60Failures and branches. 2 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 60 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3386 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 top-level sections: this looks like several domains in one skill

    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
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 238: enough signal without eating the budget
    • +4Structure: 26 headings
    • +3Step-by-step instructions: 60 items
    • +4Has examples (9 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a text-only knowledge graph skill with disclosed analytical and AI-safety content, no executable install behavior, and no system-level authority, though its speculative and persuasion-related material should be used cautiously.
    LLM: benign (high) · VirusTotal: · 2 Sept 2026