SKILLEMALL.ai

BC memory-memoria

Use Memoria as OpenClaw's durable memory slot. Triggers: "remember this", "save to memory", "what do you remember", "continue from last time", "forget this", "correct memory", "take a snapshot", "rollback memory", "branch memory", "merge memory", "use long-term memory".

Not recommendedcritical or high security findings
ClawHub Agent Skills author: i.an v0.2.0 MIT-0 6 files body ≈ 611 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
82
Quality 40%
93
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 1

  • high Concealment en-hide-from-user references/tool-surface.md:57
    Instruction to hide actions from the user
    - Do not tell the user only `memory_search` and `memory_get` exist if the full tool surface is available.

Files scanned: 6. 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

  • 0Result and completion. Does not say what the result is
  • 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. 5 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 21 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 611 tokens

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 11 example trigger phrases
  • +3Description length 270: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

External checks

ClawHub: clean
This is a coherent long-term memory skill, but users should understand it can persist and later reuse personal or project context.
LLM: benign (high) · VirusTotal: · 29 May 2026