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unbounded-consumption

Hunt LLM unbounded consumption (OWASP LLM10:2025) — denial-of-wallet and denial-of-service against LLM endpoints via unrestricted prompt size, runaway tool loops, expensive model selection, and unauthenticated fan-out.

67

Quality

81%

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SecuritybySnyk

Critical

Do not install without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

88%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 dense, highly actionable security-testing skill with executable commands, an explicit validation contract, and a clear sequenced workflow. The only soft spot is mild conciseness padding in the framing prose and a single-file layout that leaves minor progressive-disclosure headroom.

DimensionReasoningScore

Conciseness

Mostly lean and actionable with minimal over-explanation of concepts Claude already knows; only the opening framing paragraph and a few prose passages could be trimmed further.

4 / 5

Actionability

Fully executable guidance throughout: copy-paste bash grep commands in the audit workflow and concrete curl/python PoC payloads covering the common attack cases.

5 / 5

Workflow Clarity

Clear sequenced methodology (recognize → audit → exploit → validate → score → chain) with an explicit validate_finding contract (success/negative patterns) and a per-endpoint checklist, satisfying the validation requirement for destructive/batch testing.

5 / 5

Progressive Disclosure

Well-organized into eight clearly headed sections and self-contained with no nested references; minor gap is that the CVSS table and detailed PoCs could optionally be split into reference files, but the single-file structure is appropriate for a focused methodology.

4 / 5

Total

18

/

20

Passed

Description

75%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 specific, distinctive description with strong concrete vectors, but it omits an explicit 'Use when' trigger clause in the description field, capping completeness. Adding an explicit trigger clause would lift the weakest dimension.

Suggestions

Append an explicit 'Use when ...' clause to the description (e.g. 'Use when testing LLM endpoints for denial-of-wallet, rate-limit bypass, or runaway agent loops') so completeness is not capped at 3.

Add a few more natural trigger synonyms users say ('rate limiting', 'token budget', 'cost cap', 'agent loop') to broaden trigger_term_quality toward 5.

DimensionReasoningScore

Specificity

Lists multiple concrete attack vectors — 'unrestricted prompt size, runaway tool loops, expensive model selection, and unauthenticated fan-out' — giving comprehensive coverage of the unbounded-consumption domain rather than vague language.

5 / 5

Completeness

The 'what' is explicit and concrete, but the description field itself lacks a 'Use when...' clause or equivalent explicit trigger guidance; per the rubric this caps completeness at 3, and the when_to_use trigger guidance lives in metadata rather than the description.

3 / 5

Trigger Term Quality

Good keyword coverage with synonyms ('denial-of-wallet', 'denial-of-service', 'DoS', 'OWASP LLM10') that security testers would naturally say, though a few common variations (e.g. 'rate limiting', 'token budget') are absent.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (OWASP LLM10:2025 unbounded consumption) with distinct, specific triggers that are unlikely to fire for unrelated AI-security skills.

5 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
PurpleAILAB/Decepticon
Reviewed

Table of Contents

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