SKILLEMALL.ai

AC decision-tree

Activate when: user says 'help me choose between two options with different risks', 'I need to map out what could happen if we go with X', 'we have a sequential decision — first we do A then depending on results we do B', 'what is the expected value of this investment given uncertain demand'. Do NOT activate when: the decision is a one-shot choice with no sequential stages (use simple EV instead); probabilities cannot be estimated even roughly and uncertainty is too deep to quantify. More: deciqai.com/c/decision-tree

ClawHub Agent Skills author: deciqAI v1.0.5 MIT-0 6 files body ≈ 1 931 tokens Open the sourceclawhub.ai analyzed 21 h ago

Activate when: user says 'help me choose between two options with different risks', 'I need to map out what could happen if we go with X', 'we have a…

As a process C 58/100 · Has gaps — weak spots: inputs and preconditions, running it twice, progress reporting

ProcedureFinanceOperations and projectsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
58/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 6. 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 58/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 27 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1931 tokens
    • low 10 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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 522: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 27 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This is a markdown-only decision-analysis skill with no executable behavior, persistence, credential use, or hidden data access.
    LLM: benign (high) · VirusTotal: · 16 Jul 2026