SKILLEMALL.ai
RU Sign in

AC Learn

This skill should be used when the user asks to "record what we learned", "save lessons", "knowledge capture", "reflect on what happened", "write down experience", "what did we learn", "lessons learned", "retrospective", "log this plan", "what were we doing", "save plan log", or after completing a task that involved trial and error.

ClawHub Agent Skills author: Futurize Rush v0.2.0 MIT-0 2 files body ≈ 1 893 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

GeneratorLearningInfrastructuretype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 2. 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)

    Process rating: all ten parameters 56/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (Learn) differs from the folder (learn-reflect)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 100Steps. 44 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 1893 tokens
    • 100Progress reporting. Reports progress

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 11 example trigger phrases
    • +3Description length 334: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 44 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    This instruction-only learning skill is coherent, but it can automatically create persistent notes about user work without enough consent, scoping, or redaction guidance.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026