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veto_status

Read-only

Returns server status, version, and database info. Provide token count to auto-save session context when usage reaches 70%.

Instructions

Returns Veto server status, version, and database info. Pass token_count to trigger auto-save if context usage crosses 70%.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional: specific model ID (e.g. "claude-sonnet-4-6", "gemini-3.5-pro", "gpt-5.1"). When provided, Veto resolves the exact context window for that model instead of using the platform default.
platformNoAI platform (claude, gemini, codex). Used to select the correct context window for threshold calculation. Defaults to "claude".
token_countNoCurrent session token count. If provided and context usage ≥ 70%, Veto auto-saves the last known session context in the background.
Behavior1/5

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

Annotation says readOnlyHint=true, indicating no side effects, but description states token_count triggers auto-save, a side effect. This is a clear contradiction, so score is 1.

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 purpose, second sentence adds key usage detail. No redundant information.

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

Completeness3/5

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

No output schema, so description should explain return values. It vaguely says 'server status, version, and database info' without specifics. Does not cover what happens after auto-save trigger or how to interpret results.

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%, baseline 3. Description adds value by explaining that token_count triggers auto-save when context usage exceeds 70%, which is not in the schema. Other parameters (model, platform) are not further elaborated.

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 it returns Veto server status, version, and database info. Uses specific verb 'Returns' and resource 'Veto server status'. Distinguishes from siblings like veto_health by focusing on status and auto-save trigger.

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

Usage Guidelines3/5

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

Implied usage when server status is needed, but lacks explicit guidance on when to use vs. siblings like veto_health or veto_autosave_status. Provides specific scenario for passing token_count, which is helpful.

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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