BB relentless-operator
Turns your OpenClaw agent into a relentless, self-improving operator that takes any mission and executes it obsessively until completion — while automatically getting smarter and more efficient with every task.
As a process B 68/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting
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.
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 · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Implicit map keys need to be followed by map values at line 3, column 1: version: 1.0.0 ) ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 210 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
Process rating: all ten parameters 68/100
- 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
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 100Tools and files. No external tools needed
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 864 tokens
- 100Running it twice. No mutating operations
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 210: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 32 items
- +3Output format is stated explicitly
Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.
External checks
ClawHub: clean
This is a prompt-only productivity skill that uses aggressive mission-execution language, but it contains no hidden code, credential access, persistence mechanism, or data exfiltration path.
LLM: benign (high) · VirusTotal: · 29 May 2026