SKILLEMALL.ai

AB memory-distiller

Distill repeated user preferences, successful patterns, and durable working rules into reusable memory notes or prompt-ready context blocks. Use when a user wants to capture habits, preserve preferences, summarize lessons from prior work, or convert raw conversation/task outcomes into structured memory.

ClawHub Agent Skills author: danxbuidl v0.1.0 MIT-0 5 files body ≈ 1 614 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 71/100 · Nearly there — weak spots: inputs and preconditions, consistency, running it twice

GeneratorAI and agentsInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
B
71/100
Nearly there
Inputs and preconditions w 11
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: 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 71/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 40Consistency. Frontmatter name (memory-distiller) differs from the folder (danxbuidl-memory-distiller)
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 5 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 102 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 1614 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

    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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 304: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 102 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This is an instruction-only memory helper that is aligned with its stated purpose, with no evidence of hidden execution or automatic persistence.
    LLM: benign (high) · VirusTotal: · 29 May 2026