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misinformation

Hunt LLM misinformation / overreliance (OWASP LLM09:2025) — confident-but-wrong outputs that flow into downstream automated decisions, compliance reports, customer communications, or autonomous code commits without verification.

64

Quality

78%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./packages/decepticon/decepticon/skills/standard/analyst/misinformation/SKILL.md
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.

The body is tight, well-structured, and highly actionable with concrete commands, PoCs, and a validation contract. The only gap is that PoC helper functions are undefined, slightly reducing copy-paste readiness.

DimensionReasoningScore

Conciseness

Lean and efficient throughout — "LLMs are confident liars by default" — with no explanation of concepts Claude already knows and every section earning its place; the body assumes Claude's competence.

5 / 5

Actionability

Provides concrete, runnable grep commands and a Python PoC with specific thresholds (>5%), but the PoC relies on undefined helpers (ask_codegen, on_pypi, extract_imports) that read as pseudocode rather than copy-paste-ready code — minor gaps.

4 / 5

Workflow Clarity

The audit workflow is a clear sequenced procedure with a validation checkpoint via the validate_finding contract (success/negative patterns), but the per-sink questions are framed as loose prompts rather than an explicitly numbered validate-then-act loop.

4 / 5

Progressive Disclosure

A single self-contained file with well-organized numbered sections and no nested or buried references; no bundle files are present, so the simple-skill exception applies and the clean organization scores 5.

5 / 5

Total

18

/

20

Passed

Description

70%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.

The description is specific and occupies a distinct niche with good trigger terms, but it lacks an explicit 'Use when...' activation clause, capping its completeness. Adding a concrete usage-trigger sentence would round it out.

Suggestions

Append an explicit 'Use when ...' trigger clause naming concrete scenarios (e.g., 'Use when auditing agentic pipelines, auto-decision endpoints, or code-gen auto-deploy workflows for unverified model output').

Add natural synonyms users say out loud — 'hallucination', 'model hallucinating', 'unverified AI output' — to broaden trigger-term coverage.

Lead with the highest-impact action verb phrase before the enumeration so the 'what' lands in the first clause.

DimensionReasoningScore

Specificity

Names the domain and several concrete targets — "downstream automated decisions, compliance reports, customer communications, or autonomous code commits" — listing multiple specific actions with only minor coverage gaps, fitting the anchor 4 example.

4 / 5

Completeness

The 'what' is explicit and concrete, but there is no 'Use when...' or equivalent explicit trigger clause in the description itself (only the implicit metadata.when_to_use), which per the judging guidelines caps completeness at 3.

3 / 5

Trigger Term Quality

Good natural keyword coverage ("LLM misinformation", "overreliance", "confident-but-wrong output", "OWASP LLM09") a user would actually say, though common synonyms like "hallucination" are absent — solidly above the midpoint but not comprehensive.

4 / 5

Distinctiveness Conflict Risk

Clear niche (OWASP LLM09:2025 misinformation / overreliance) with distinct, specific triggers and minimal overlap risk with other skills.

5 / 5

Total

16

/

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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