SKILLEMALL.ai

AF claude-code-memory

Use when you want to set up, maintain, or review a Claude Code style layered memory workflow, including `CLAUDE.md` rules, session memory, durable memory, and promotion of stable learnings into instruction files.

ClawHub Agent Skills author: Liu Wenyu v0.1.0 MIT-0 12 files body ≈ 1 459 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 41/100 · Will not run — References files that are not bundled: testing-policy.md

AnalyzerAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
82
Run on models
none yet
Process rating
F
41/100
Will not run
References files that are not bundled: testing-policy.md
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The text references files that are not there: add them or drop the references.
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

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-agent-memory-dump examples/persistent-memory/MEMORY.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    examples/persistent-memory/MEMORY.md

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: testing-policy.md

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: testing-policy.md
  • 0Tools and files. 1 referenced file(s) missing: testing-policy.md
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 40Consistency. Frontmatter name (claude-code-memory) differs from the folder (claude-code-memory-skill)
  • 55Failures and branches. 1 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 60 steps
  • 100Execution cost. Instruction body is 1459 tokens
  • low 12 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 212: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 60 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

External checks

ClawHub: clean
This is a documentation-only memory workflow skill that openly stores repo-local agent notes, with privacy hygiene users should manage themselves.
LLM: benign (high) · VirusTotal: · 29 May 2026