BC soul-weaver
AI Soul Weaver - 12 Curated Celebrity Templates + Custom Generation. Generate OpenClaw agent configurations through dialog or select from 12 world-famous tech & business leaders.
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Broad scope
meta-agent-memory-dumptemplates/performance/jensen-huang/HEARTBEAT.mdAgent memory / workspace files bundled with the skill (32) — likely a workspace dump with personal data or tokenstemplates/performance/jensen-huang/HEARTBEAT.md, templates/performance/jensen-huang/IDENTITY.md, templates/science/alan-turing/HEARTBEAT.md, templates/science/alan-turing/IDENTITY.md, templates/scienc
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low Risky intent
intent-offensive-securitytemplates/startup/elon-musk/SECURITY.md:39Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Penetration testing
Files scanned: 78. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 178 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "permissions" - note
frontmatter-keyunknown frontmatter key "platform"
Process rating: all ten parameters 53/100
- 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. 3 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 34 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1826 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
- +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
- -223 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 178: enough signal without eating the budget
- +4Structure: 32 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.