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temurkhan13

openclaw-output-vetter-mcp

review_transcript

Detects unverified completion claims, cross-turn contradictions, and tool calls without observable effects in AI agent transcripts.

Instructions

Multi-turn agent transcript review — flags unverified completion claims (assistant says 'I've configured X' with no supporting tool calls), cross-turn factual contradictions, and tool calls without observable side effects. Pass an array of {role, text, tool_calls?} objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transcriptYesList of turns. Each: {role, text, tool_calls?}
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses the tool's behavior: it flags specific types of issues (unverified claims, contradictions, tool calls without side effects). No mention of destructive actions or auth needs, but for a review tool this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with key purpose and specific detection criteria. No redundant or unnecessary words. Efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has one parameter, no output schema. Description explains input and detection criteria well, but could mention the output format (e.g., list of issues) for completeness. Still adequate for the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for the transcript items. The description adds value by explaining the structure and purpose of the parameter ('Pass an array of {role, text, tool_calls?} objects'). It clarifies the expected input beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool's purpose: reviewing multi-turn agent transcripts for specific issues (unverified claims, contradictions, tool calls without side effects). It distinguishes from sibling tools like find_swallowed_exceptions and verify_action_outcome by focusing on transcript analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies usage for analyzing agent transcripts and lists what it detects, but does not explicitly state when to use this tool versus alternatives or when not to use it. The context of sibling tools helps, but explicit guidance would improve.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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