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llm-redteam

LLM application red-teaming — prompt injection (direct + indirect), jailbreak, system-prompt leak, data exfiltration, guardrail bypass, multi-turn crescendo, cross-lingual + cipher + invisible-unicode token smuggling, excessive agency / tool abuse, insecure output handling. Canonical OWASP LLM Top 10 + ASI01-ASI10 mapping. Use when a target exposes a chat/completions/assistant/copilot endpoint, an AI feature that consumes user text or documents, or any /v1/chat, /api/chat, /mcp surface.

74

Quality

93%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tight, routing-style skill that stays actionable through concrete commands, a canonical ASI table, and strong false-positive discipline. The main gaps are minor token redundancy in the attack-class glosses and confirmation messaging, and the absence of one explicit end-to-end procedure.

Suggestions

Trim the one-line glosses for classes Claude already knows (jailbreak, cross-lingual, cipher-obfuscation) down to just the payload style the corpus fires, or drop them and rely on --list-categories.

Consolidate the action-vs-echo rule stated in the epigraph, §0, §2 and §5 into one section to remove redundancy.

Add a short ordered procedure (route → run category → check kill criteria → confirm canary/OOB/sink → chain → report) so the numbered sections read as one workflow with a kill/confirm loop.

DimensionReasoningScore

Conciseness

Dense, table-driven and mostly lean, but it spends tokens restating knowledge Claude already has (e.g. 'cross-lingual — override instruction in another language to dodge English-only filters', 'leetspeak / ROT13-wrapped instruction') and repeats the action-vs-echo discipline in the epigraph, §0, §2 and §5.

4 / 5

Actionability

Gives copy-paste-ready commands covering the common cases ('--url <endpoint> --field <json-field>', the OpenAI-style --template with --response-path choices.0.message.content, '--category jailbreak') plus concrete chaining and confirmation tooling (oob_listener.py, verifiers).

5 / 5

Workflow Clarity

Numbered sections plus a routing table imply a clear sequence, and §0/§5 act as explicit triage and confirmation checkpoints, but there is no single ordered run → confirm → chain → report procedure with a fix-and-retry loop.

4 / 5

Progressive Disclosure

A single well-organized file with no bundle directories; the payload corpus and detail are correctly externalized to the runner tool, and every external pointer (llm_redteam.py, oob_listener.py, sibling skills) is clearly signaled at one level deep.

5 / 5

Total

18

/

20

Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: comprehensive, specific, third-person, with an explicit 'Use when' clause covering endpoint, feature, and API-surface triggers. The only weakness is a minor trigger overlap with the sibling MCP-audit skill.

DimensionReasoningScore

Specificity

Enumerates the full set of concrete attack classes ('prompt injection (direct + indirect), jailbreak, system-prompt leak, data exfiltration, guardrail bypass, multi-turn crescendo, cross-lingual + cipher + invisible-unicode token smuggling, excessive agency / tool abuse, insecure output handling') plus a canonical OWASP ASI01-ASI10 mapping — comprehensive with no coverage gaps.

5 / 5

Completeness

Explicitly answers both: what it does (the enumerated attack classes and ASI mapping) and when to use it ('Use when a target exposes a chat/completions/assistant/copilot endpoint, an AI feature that consumes user text or documents, or any /v1/chat, /api/chat, /mcp surface').

5 / 5

Trigger Term Quality

Includes the natural terms a user or model would say (prompt injection, jailbreak, red-teaming, AI feature) plus endpoint synonyms and concrete surfaces: 'chat/completions/assistant/copilot endpoint' and '/v1/chat, /api/chat, /mcp surface'.

5 / 5

Distinctiveness Conflict Risk

It carves out a clear LLM red-team niche distinct from generic web or doc skills, but the '/mcp surface' trigger overlaps with the sibling mcp-server-audit skill that the body itself routes MCP-server audits to, leaving minor conflict risk with a closely related skill.

4 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Awarexone/Agentic-Bug-Hunter

Path

skills/llm-redteam/SKILL.md

Reviewed

Table of Contents

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