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veto

by jigyasudham
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TypeScript
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veto_status

Read-only

Check server status, version, and database info. Supply current token count to auto-save session context when usage reaches 70%, reducing lost work.

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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.8.0
    • changedInput schema / properties / platform / enum
      Previous value: -[
-  "claude",
-  "gemini",
-  "codex"
-]New value: +[
+  "claude",
+  "gemini",
+  "codex",
+  "antigravity"
+]
  2. First observedv2.7.1

TDQS

A3.8/5.0
Behavior4/5

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

The readOnlyHint annotation already tells the agent this is a safe read, and the description adds a genuinely non-obvious behavioral trait: an unconditional-looking status call can trigger a background auto-save when token_count is supplied and usage is ≥70%. That side effect is disclosed rather than hidden, which is exactly the kind of context annotations cannot convey; it stops short of 5 because no auth, rate-limit, or failure behavior is described.

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, zero filler, and the primary capability is front-loaded ahead of the conditional side-effect clause. Every clause carries information the agent can act on.

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 low-complexity status tool with no output schema and full schema coverage, the description covers purpose and the notable side effect. The remaining gap is sibling disambiguation within a very crowded veto_* status family, which is the one thing an agent still has to guess at.

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 description coverage is 100% and all three parameters are already documented, including the token_count threshold and the model/platform context-window resolution. The description restates the token_count rule but adds no syntax or edge-case detail beyond the schema, so the baseline of 3 applies.

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

Purpose4/5

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

The description names a specific verb and resource set — server status, version, and database info — so the agent knows exactly what comes back. It does not, however, differentiate this from close siblings like veto_health, veto_usage_status, or veto_context_status, which an agent would need to disambiguate among.

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?

One concrete usage instruction is given (pass token_count to trigger auto-save when context usage crosses 70%), which is more than many peers offer. But there is no statement of when to prefer this tool over veto_health/veto_usage_status/veto_autosave_status, so routing among the status family is left to inference.

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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