SKILLEMALL.ai

AC beastxa-memory-pro

Production-grade memory system for OpenClaw agents. Auto-organizes notes into topic files, prevents context loss during compaction, and runs daily/weekly maintenance crons. Zero external dependencies — pure local Markdown files. Install and forget. Use when: agent keeps forgetting context, MEMORY.md is too large, notes are disorganized, or you want automatic memory maintenance without manual effort.

ClawHub Agent Skills author: tzx666888 v1.0.0 MIT-0 13 files · 2 scripts body ≈ 838 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
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: 13. 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 53/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 838 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 4 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 402: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (5 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

    External checks

    ClawHub: suspicious
    The skill appears to be a local memory helper, but its installer makes persistent global OpenClaw changes and scheduled background edits without enough user control or warning.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026