BC ship-safe-red-team
Run a multi-agent red team scan — 29 specialized security agents scan for 80+ attack classes including injection, auth bypass, SSRF, supply chain, Supabase RLS, MCP security, agentic AI, RAG poisoning, PII compliance, and more. Use when the user wants a deep security analysis beyond just secrets.
Run a multi-agent red team scan — 29 specialized security agents scan for 80+ attack classes including injection, auth bypass, SSRF, supply chain, Supabase…
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 · 4
✓ No critical or high findings
Medium and low: 4
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low Risky intent
intent-offensive-securitySKILL.md:3Offensive-security / dual-use content (legitimate for authorised testing; review intended use)description: Run a multi-agent red team scan — 29 specialized security agents scan for 80+ attack classes including injection, auth bypass, SSRF, supply chain, Supabase RLS, MCP security, agentic AI,
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low Risky intent
intent-offensive-securitySKILL.md:7Offensive-security / dual-use content (legitimate for authorised testing; review intended use)# Ship Safe — Red Team Scan
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low Risky intent
intent-offensive-securitySKILL.md:9Offensive-security / dual-use content (legitimate for authorised testing; review intended use)You are running a multi-agent red team scan using Ship Safe's 29 security agents.
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low Risky intent
intent-offensive-securitySKILL.md:11Offensive-security / dual-use content (legitimate for authorised testing; review intended use)## Step 1: Run the red team scan
Files scanned: 1. 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 62/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 55Failures and branches. 1 branches
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 645 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
- +1No license
- +2Single-language instructions
- +3Description length 297: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.