SKILLEMALL.ai

AB learning-loop-skill

Autonomous structured learning for mastering complex topics through cron-based 5-session feedback loops. Use when user wants to deeply learn a subject (e.g., "learn X", "teach me Y", "master Z", "deep dive into X", "I want to understand X deeply"). NOT for quick overviews, simple factual questions, or topics without clear right/wrong answers.

ClawHub Agent Skills author: Sagar v1.0.0 MIT-0 8 files · 2 scripts body ≈ 2 037 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 71/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
100/100
safety, quality, tests
Safety 60%
100
Quality 40%
100
Run on models
none yet
Process rating
B
71/100
Nearly there
Result and completion w 14
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: 8. 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 71/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 17 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 27 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2037 tokens

    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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 344: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 2 scripts are documented

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

    External checks

    ClawHub: suspicious
    This skill does what it says, but it can create self-extending scheduled agent jobs that keep running after the initial setup.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026