SKILLEMALL.ai

AB complexity-cuts

Lower Big-O on existing code via a one-transformation-at-a-time playbook with verify-revert-stop. For new code use lemmaly; for math-level wins escalate to mathguard.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 3 629 tokens Open the sourcegithub.com analyzed 2 d ago

Lower Big-O on existing code via a one-transformation-at-a-time playbook with verify-revert-stop.

As a process B 73/100 · Nearly there — weak spots: inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
B
73/100
Nearly there
Inputs and preconditions w 11
0
When it triggers w 12
50
Failures and branches w 10
55
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills

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: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "source_repo"
    • note frontmatter-key unknown frontmatter key "source_type"
    • note frontmatter-key unknown frontmatter key "date_added"
    • note frontmatter-key unknown frontmatter key "tools"
    • note frontmatter-key unknown frontmatter key "license_source"

    Process rating: all ten parameters 73/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 65 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3629 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low 14 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
    • +4Description does not say when NOT to use the skill (false activations)
    • -5TODO / placeholder text left in the skill
    • +2Single-language instructions
    • +3Description length 166: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 65 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.