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veto_prompt_optimizer

Read-only

Analyzes prompts for failure modes (vague role, missing output format, injection-prone, no examples) and rewrites to improve quality. Uses a local agent loop, no API keys required.

Instructions

Scores a prompt for failure modes (vague role, missing output format, injection-prone, no examples) and returns a rewritten version with improvements. Zero API keys needed — uses the local agent loop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoOptional — what the prompt is trying to accomplish.
roleNoOptional — 'system' | 'user' (helps tailor analysis).
promptYesThe prompt to optimize (system or user prompt).
agent_responseNoPhase 2 response from the host AI (JSON). Pass this back when prompted by the server to complete the agentic loop.
Behavior4/5

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

The description adds behavioral context beyond the readOnlyHint annotation, specifying that it uses a local agent loop and requires no external resources. No contradictions.

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?

The description is extremely concise: two sentences that convey the core function and a key benefit (no API keys). Every word earns its place.

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?

Given the tool has 4 parameters (1 required) and no output schema, the description provides sufficient context about inputs and outputs (scores and rewritten version). It could specify the output format, but the description is adequate.

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?

All parameters have schema descriptions (100% coverage). The description adds value by explaining the 'agent_response' parameter's role in the agentic loop and the tool's overall purpose, complementing 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?

The description clearly states it scores a prompt for failure modes and returns a rewritten version. It uniquely identifies the tool's function among a large set of unrelated siblings.

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?

The description explains the tool's use case (optimizing prompts) and notes that no API keys are needed. It does not explicitly contrast with siblings or state when not to use, but the context is clear.

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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