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Ask many questions about one state

jev_ask
Read-onlyIdempotent

Get answers to several independent questions about the same document or state in a single call, reducing cost and latency. Provide paths for server-side file reading and receive only conclusions.

Instructions

Ask several independent questions about the same state in ONE request. Jev prefills the state once and scores every question in a single forward pass, so extra questions add almost no latency. Prefer this over repeated single-question calls: on a document-dominated workload it is dramatically cheaper and faster with no change in answers. Questions cannot see each other's answers, so state any speculative premise explicitly and let your own logic decide which answers apply. Pass 'paths' instead of 'state' to ask about files without reading them yourself: the server reads them, Jev sees them as one state keyed by path, and only the answers enter your context. Name the file in a question with its path in backticks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathsNoFiles to read inside the server instead of state. Up to JEV_MAX_ITEMS; together they must fit JEV_MAX_STATE_CHARS. Same rules as jev_triage paths: below an allowed root, never credential files, contents never returned.
stateNoThe content to evaluate, when you already hold it. Supply exactly one of state or paths.
act_aboveNoConfidence at or above which the answer is marked 'act'. Default 0.8. Calibrate on your own data and the cost of being wrong.
questionsYes
review_aboveNoConfidence at or above which the answer is marked 'review' rather than 'abstain'. Default 0.5.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNoWith paths: what was read, as sizes only.
modelYes
usageYes
answersYesKeyed by your question ids. Choice and Score answers also carry an 'action' gated on confidence.
latency_msYesWall-clock milliseconds for the API round trip, for your own calibration logs.
none_optionsYesFor each 'classify' question, the key carrying the no-match meaning, or null.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.14.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already provide readOnly, idempotent, and non-destructive hints, so the description adds genuinely useful behavioral context beyond them: Jev prefills the state once, extra questions add almost no latency, paths are read server-side and keyed by path, and only answers enter the agent's context. These are non-obvious behaviors that materially affect invocation decisions.

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?

The description is dense but every sentence earns its place: batching benefit, performance trade-off, question independence caveat, the paths alternative, context containment, and file-naming guidance. Core purpose is front-loaded and the rest builds on it without repetition or filler.

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

Completeness5/5

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

For a tool with five parameters and an existing output schema, the description covers the essential selection and invocation context: when to prefer batching, how paths differ from state, the independence limitation, and how to phrase file references. The output schema handles return-value details, so nothing critical is missing for correct use.

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 high at 80%, so the schema carries most parameter meaning, but the description adds real value: it explains the semantic difference between 'state' and 'paths', notes that the server reads paths and treats them as one state keyed by path, and gives the concrete guidance to name files with their path in backticks. This goes beyond the structured schema descriptions.

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 uses a specific verb ('Ask') and resource ('several independent questions about the same state'), and immediately distinguishes the tool from repeated single-question calls by emphasizing ONE request and a single forward pass. It clearly conveys what the tool does and how it differs from the surrounding single-question sibling tools.

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?

It explicitly says 'Prefer this over repeated single-question calls' and gives concrete conditions for when to use 'paths' instead of 'state'. It also states that questions cannot see each other's answers, which tells the agent to avoid this tool when questions are dependent, even though it doesn't name an alternative explicitly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.