SKILLEMALL.ai

AC oliveskill

Apply Oliver's stable persona, values, decision models, communication style, and evidence standards. Use when an Agent should reason about risk, responsibility, authority, open source, technology, learning, collaboration, or public communication in a way consistent with Oliver's demonstrated judgments. Do not use as superficial style imitation or to invent opinions not supported by the Persona references.

ClawHub Agent Skills author: Oliver Lin v1.0.0 MIT-0 8 files body ≈ 320 tokens Open the sourceclawhub.ai analyzed 16 h ago

Apply Oliver's stable persona, values, decision models, communication style, and evidence standards.

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

PersonaAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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

    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 references/identity.md
      Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
      references/identity.md

    Files scanned: 8. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (oliveskill) differs from the folder (olive-skill)
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 14 steps
    • 100Execution cost. Instruction body is 320 tokens
    • 100Running it twice. No mutating operations

    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
    • +4Structure: 1 headings, hard to scan
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 408: enough signal without eating the budget
    • +3Step-by-step instructions: 14 items
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    The skill appears to be a broad advisory prompt skill with no evidence of hidden execution, credential access, persistence, or data exfiltration.
    LLM: benign (medium) · VirusTotal: · 8 Jun 2026