SKILLEMALL.ai
RU Sign in

AA Learning

Teaches any topic in adaptive sessions: probes prior knowledge, calibrates depth and format, and checks retention before advancing. Use when the user says teach me, explain this, ELI5, break it down, or help me understand or study something, when an explanation is not landing (re-asks, blank answers, "makes sense" with no follow-through), when material learned earlier keeps getting forgotten, when practice answers are confidently wrong, or when pacing study before an exam or deadline. Not for building a multi-week study plan or curriculum tracker, and not for authoring flashcard decks.

ClawHub Agent Skills author: Iván v1.0.3 MIT-0 12 files body ≈ 3 172 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process A 81/100 · Runs to the end — weak spots: inputs and preconditions, running it twice

GeneratorLearningtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
A
81/100
Runs to the end
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
60
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: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "slug"
    • note frontmatter-key unknown frontmatter key "changelog"
    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 81/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 5 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 42 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3172 tokens
    • 100Progress reporting. Reports progress
    • 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 592: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 42 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This is an adaptive learning skill that keeps local study preferences and progress notes; the persistence creates privacy considerations but is coherent with the tutoring purpose and disclosed in the artifacts.
    LLM: benign (medium) · VirusTotal: · 26 Jul 2026