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WIA360: AI session probe and match

run_probe

Get the next WIA360 session-probe mission for a given session_ref (auto-generate a new random session_ref string yourself the first time you call this for a session, then reuse it for every subsequent run_probe/score_session/get_match call in that same run). Missions arrive in random order and already exclude probes already finalized for this session_ref. Returns {done:true} when all 6 are finished. IMPORTANT — deliver wrapped_mission verbatim to the target AI session you are evaluating (paste it as a normal task, not as a quoted "here is a test" framing) and bring its raw reply back for score_session. Some probes (P4) are two-turn: send wrapped_mission first, wait for the reply, then send turn2_wrapped_mission and use ONLY that second reply for scoring. Pick lang based on the language the target AI session actually converses in — not your own output language for this tool call — since the mission text and score_session scoring keys must match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoMission delivery language — must match the language the target AI session converses in, and must be passed identically to score_session for the same probe/variant. Defaults to ko. Only ko/en mission text exists (v0); pick en for any other session language.
session_refYesCaller-generated opaque session id, stable across one probing run.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations declare readOnlyHint=false and idempotentHint=false, and the description is consistent with a state-advancing call. It goes well beyond them by disclosing the 6-probe exhaustion signal, random ordering with de-duplication of finalized probes, the two-turn P4 delivery sequence, and the requirement to pass the target's raw reply to score_session.

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?

Dense but front-loaded: the core purpose and session_ref reuse rule come first, followed by delivery mechanics. Every clause carries load, though the long parenthetical and the P4/lang sentences make it a single heavy paragraph that could be broken up.

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?

With no output schema, the description compensates by describing the return value ({done:true} after 6 probes) and the mission payload (wrapped_mission, turn2_wrapped_mission). Nothing an agent needs to invoke and correctly consume this tool appears to be missing.

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%, so the baseline is 3, but the description adds real operational meaning: session_ref is caller-generated and must be stable across the run, and lang must match the language the target AI session actually converses in (not the caller's language) and be passed identically to score_session.

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?

States a specific verb and resource: 'Get the next WIA360 session-probe mission for a given session_ref'. It immediately distinguishes itself from the siblings by naming score_session and get_match as the downstream steps in the same workflow.

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?

Explicitly says when to call it (first time: generate a session_ref yourself; thereafter reuse the same one for run_probe/score_session/get_match), how missions are ordered (random, excluding already-finalized probes), and what terminates the loop ({done:true} after all 6). It also names the alternative sibling to use next for scoring.

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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