SKILLEMALL.ai

AC basic-memory

Gives your OpenClaw agent persistent memory across conversations by organizing entries in the native MEMORY.md and daily memory files. Automatically loads saved context at session start and saves important facts, decisions, and preferences during conversation. Use this skill whenever users say 'remember this', 'save this', 'don't forget', 'note that', 'what do you remember', 'forget [topic]', or when you detect they've shared something worth keeping — even if they don't explicitly ask. Also activate automatically at the start of every new session to load prior context.

ClawHub Agent Skills author: billyhetech v1.0.0 MIT-0 3 files body ≈ 1 157 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
58/100
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: 3. 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 58/100

    • 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. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1157 tokens
    • 100Progress reporting. Reports progress
    • 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 575: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a disclosed memory-management skill that persists user context locally, but it may save personal details automatically unless the user limits that behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026