SKILLEMALL.ai

AC self-improving

Global, namespaced learning memory for OpenClaw. Use when users correct output, set stable preferences, ask what was learned, ask for memory stats, or request forgetting learned patterns. Keep memory cross-session, avoid context mixing, and enforce strict privacy boundaries.

ClawHub Agent Skills author: Mark Lee v0.1.0 5 files body ≈ 642 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency

ProcedureSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
61/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 5. 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 61/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (self-improving) differs from the folder (self-improving-global-safe)
    • 60Result and completion. Output format stated, no completion criterion
    • 65Failures and branches. 3 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 23 steps
    • 100Execution cost. Instruction body is 642 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (6 tags): a typed call is more reliable

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 275: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 23 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a disclosed local memory helper that stores and manages user-approved preferences in a named folder, with no executable code or network behavior found.
    LLM: benign (high) · VirusTotal: · 29 May 2026