SKILLEMALL.ai

AC hui-yi

Trigger for cold-memory recall and archive work under memory/cold/. Use only for explicit requests about older low-frequency context, historical continuity, resurfacing, cooling, rebuild, and repetition-driven reinforcement — not for any casual mention of words like "archive" or "remember". Do not use for fresh daily notes, stable high-frequency facts, tooling/setup notes, or unvalidated new learnings. Also covers an optional opt-in hook (installed via scripts/install_hook.py, enabled in openclaw.json only with --enable) that accumulates Session signals from recall-related turns into memory/cold/ notes and tags.json.

ClawHub Agent Skills author: Fue Tsui v1.2.11 MIT-0 36 files body ≈ 758 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 36. 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 56/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 43 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 758 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

    • +3Output format is not stated: the model decides each time
    • -45 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 624: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 43 items
    • +4Has examples (1 code blocks)
    • +3All 11 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    Hui-Yi is a disclosed local cold-memory tool with an optional opt-in hook that persists memory-use signals, so it should be enabled deliberately but does not show malicious behavior.
    LLM: benign (high) · VirusTotal: · 10 Jun 2026