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BC auto-memory

Indestructible agent memory — permanently stored, never lost. Save decisions, identity, and context as a memory chain on the Autonomys Network. Rebuild your full history from a single CID, even after total state loss.

ClawHub Hermes author: 0xautonomys v1.1.0 MIT-0 13 files · 8 scripts body ≈ 2 746 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
89
Quality 40%
71
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: auto-memory (ClawHub)

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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(curl:*)
    allowed-tools: Bash(curl:*) Bash(jq:*) Bash(file:*) Read Write
  • medium Broad scope meta-requests-env-secret SKILL.md:1
    Skill asks the runtime to inject credential env vars into its sandbox: AUTO_DRIVE_API_KEY — verify each one is needed for the stated purpose
    required_environment_variables: AUTO_DRIVE_API_KEY
  • low Secrets in code secret-high-entropy-token references/memory-chain.md:75
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    The contract is at `0x51…A3c` on Autonomys Mainnet (Chain ID 870). It provides:
    quoted

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 217 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "required_environment_variables"

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Consistency. Frontmatter name (auto-memory) differs from the folder (permanent-memory)
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 70Failures and branches. 6 branches
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 32 steps
  • 100Execution cost. Instruction body is 2746 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
  • -43 reference files, but SKILL.md never points to them: the model will not open them
  • -32 of 8 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 217: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (11 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This skill clearly implements permanent public memory storage, and the reviewed artifacts disclose the key risks rather than hiding unrelated behavior.
LLM: benign (high) · VirusTotal: · 5 Jul 2026