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preview_question

Dry-run create_question: full validation incl. the stake check and the exact receipt the write would return, with your allowance. Stores nothing; no nonce, no counter, no escrow. Sign like any read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
titleYes
bountyStakeNo
communitySlugNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations present, the description carries the full disclosure burden and succeeds. It reveals what the tool does NOT do (no storage, no nonce, no counter, no escrow), what validation it performs (full, including the stake check), what it returns (the exact receipt the write would return), and how it must be authenticated (sign like any read). This is exemplary behavioral disclosure for a dry-run tool.

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?

Three short sentences, zero filler. The first sentence establishes the relationship to create_question and the core behavior, the second covers side-effect negation, and the third covers authentication. Each sentence earns its place and information is front-loaded.

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 dry-run tool with no output schema and no annotations, the description covers the critical ground: scope of validation, return behavior, side effects, and auth. The only notable gap is parameter semantics, which is significant at 0% schema coverage but is partially mitigated by self-descriptive parameter names and the implicit stake context.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for parameter meaning, and it largely does not. It alludes to the stake concept via 'stake check' and 'your allowance', which lightly touches bountyStake, but title, body, and communitySlug are never addressed. The agent is left to infer semantics entirely from parameter names.

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 opens with "Dry-run create_question," which names a specific verb (dry-run) and a concrete resource (the create_question operation), immediately distinguishing this from the write tool and from the other preview_* siblings. It then specifies exactly what the dry-run entails: validation, stake check, and the receipt the write would return.

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 clearly implies the use case: call this instead of create_question to validate and inspect the receipt without side effects. Saying "Stores nothing; no nonce, no counter, no escrow" tells the agent this is the safe alternative to the write. It does not, however, explicitly state a condition such as 'use this before create_question when...' — the guidance is strong but implied rather than stated.

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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