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veto_agent_plan

Read-only

Consult a specialist agent for a domain-expert execution plan. Returns approach, ordered steps, checklist, patterns, and pitfalls.

Instructions

Gets a domain-expert execution plan from a specific worker agent. Returns approach, ordered steps, checklist, patterns, and pitfalls for the task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesThe task for the agent to plan.
agentYesThe worker agent to consult.
contextNoOptional additional context.
llm_backedNoIf true, routes the task through the LLM runner for deep reasoning instead of using the deterministic pattern engine.
project_dirNoOptional: absolute path to the project directory. Auto-injects package.json, git diff, and stack info into the agent context.
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?

Annotations already declare readOnlyHint=true. The description adds value by specifying what the tool returns (approach, steps, etc.), which is consistent with read-only behavior. 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?

Two sentences, front-loaded with the action and result. No redundant words. Efficient and clear.

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?

For a tool with 6 parameters and full schema coverage, the description covers the main purpose and return values. It could mention the domain-expert aspect more explicitly, but overall it's complete enough.

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

Parameters3/5

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

Schema coverage is 100%, so parameters are fully documented. The description does not add extra meaning beyond summarizing the tool's output, which is adequate for the baseline score of 3.

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 the tool gets a domain-expert execution plan from a specific worker agent and lists the return content (approach, steps, checklist, etc.). This distinguishes it from many sibling tools that have different purposes.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives like veto_council_debate or veto_delegate. The description only implies it's for getting a plan from a single agent, but lacks when-not or alternative references.

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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