AB ai-warden-setup
Install, configure, and manage the AI-Warden prompt injection protection plugin for OpenClaw. Publisher: AI-Warden (ai-warden.io). Source: github.com/ai-warden/openclaw-plugin. NPM: openclaw-ai-warden. Use when: (1) setting up AI-Warden on a new OpenClaw instance, (2) configuring security layers or API keys, (3) troubleshooting AI-Warden plugin issues, (4) updating the plugin, (5) checking warden status or accuracy. Triggers on phrases like "install ai-warden", "setup prompt injection protection", "configure warden", "security plugin", "protect my agent".
As a process B 66/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting
How to improve
- 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
- note
frontmatter-keyunknown frontmatter key "install"
Process rating: all ten parameters 66/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 21 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2023 tokens
- 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
- +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
- +5Description quotes 5 example trigger phrases
- +3Description length 561: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (26 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.