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Send messages to an OpenAI model and continue persistent sessions with per-call overrides, saving request IDs to recover interrupted requests.

Instructions

Ask an OpenAI model or continue a persistent session. Explicit per-call overrides; no local code or file access. Save request_id for interruption recovery.

Input Schema

NameRequiredDescriptionDefault
modelNo
messageYes
verbosityNo
request_idNo
session_idNo
timeout_msNo
instructionsNo
reasoning_effortNo
max_output_tokensNo

Output Schema

NameRequiredDescriptionDefault
statusYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior4/5

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

Annotations cover safety (readOnlyHint=false, openWorldHint=true, destructiveHint=false), and the description adds real context: no local code or file access, per-call overrides rather than stored config, and that request_id enables recovery from interruption. It does not explain error/timeout behavior despite exposing a timeout_ms parameter.

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?

Three short clauses, front-loaded with the action and continuation mode, then constraints. Dense and wasteful-free, though arguably over-compressed given the undocumented 9-parameter surface.

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

Completeness3/5

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

An output schema exists, so return values need not be described, and the safety profile is annotated. But with 9 undescribed parameters and sibling tools that overlap in purpose, the description leaves notable gaps about parameter roles and interruption/retry semantics.

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% across 9 parameters, so the description must carry the load and largely doesn't. It only gestures at session_id, request_id, and the override family; it never explains message vs instructions, verbosity, reasoning_effort, max_output_tokens, or timeout_ms semantics.

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?

States a specific verb+resource ('Ask an OpenAI model') plus the session-continuation mode, which distinguishes it from sessions and request_status. It does not explicitly name those siblings or state the boundary between chatting and managing sessions.

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?

'Continue a persistent session' and 'save request_id for interruption recovery' imply when session_id/request_id matter, but there is no explicit when-to-use guidance versus the sibling tools (e.g. use request_status instead to poll, sessions to manage sessions).

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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