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Run typed custom questions

run_questions

Validate caller-built state and typed Choice, Noul, or Score questions to return structured judgments for auditing, routing, and classification tasks.

Instructions

Typed custom path when no pack shortcut fits. Validate caller-built state plus typed Choice / Noul / Score and call the same TypeSafe System One path as run_pack. Not chat and not essay generation. Prefer run_pack when list_packs has an id (e.g. i18n_copy). Fail-closed schema: Choice is a closed option map (max 255; include a refuse key if needed), Noul is yes/no, Score is ≥2 ordered levels. Returns typed answers + usage. Requires TYPESAFE_API_KEY. No side effects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional TypeSafe model override (default JEV_MODEL / jev-latest).
stateYesCaller-built JSON evidence. Closed and small — not a repo dump.
questionsYesTyped questions: { id, type: choice|noul|score, instructions, criteria }. Not a free-form prompt.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.0.9

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden. It discloses key behaviors: 'No side effects', 'Requires TYPESAFE_API_KEY', 'Fail-closed schema', and 'Returns typed answers + usage'. It doesn't detail error handling or rate limits, but the provided information is strong for a read-like tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured: key purpose, usage guidance, schema fail-closed details, and constraints are front-loaded. Each clause adds value, though it could be slightly clearer for non-experts.

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's complexity (typed questions, nested objects) and lack of output schema/annotations, the description is quite complete. It covers prerequisites (API key), side-effect profile, and schema constraints. Missing output details are noted but acceptable due to description's stated return of 'typed answers + usage'.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is 3. The description goes beyond the schema: it explains the purpose of 'state' (caller-built, closed, small), the structure of 'questions' (typed, closed option map, max 255, include refuse key), and the semantics of Noul and Score. This adds substantial meaning for correct parameter construction.

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's purpose: to run typed custom questions via a specific path ('TypeSafe System One') when no pack shortcut fits. It distinguishes it from siblings by explicitly mentioning 'run_pack' and noting it is 'Not chat and not essay generation.'

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

Usage Guidelines5/5

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

The description provides explicit guidance: 'Prefer run_pack when list_packs has an id' and states it is not for chat or essay generation. It also describes the fail-closed schema constraints, which are critical for correct usage.

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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