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continue_chat

Used with chat_async when a large edit paused to ask whether to keep going. Poll get_job until status=awaiting_approval AND metadata.awaiting_kind='continue_prompt'; then POST here with continue=true to resume (the AI picks up where it left off with a fresh time/step budget) or continue=false to stop (everything applied so far is kept). The job then resumes/finishes and reaches status=completed. This is NOT the change- approval endpoint (that is approve_change) — it can only act on a continue-prompt pause.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID awaiting a continue decision.
continueYesTrue to resume with a fresh budget; false to stop here (work so far is kept).
session_idYes
authorizationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden but discloses strong behavioral detail: continue=true resumes with a fresh time/step budget, continue=false stops while keeping everything applied so far, and the job reaches status=completed. It omits auth/permission requirements despite an authorization parameter being present.

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?

Information-dense but well front-loaded: the trigger condition comes first, then the action, then the exclusion. Every sentence carries operational weight, though the multi-line flow is slightly long for what is essentially a poll-then-post pattern.

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 resume/stop control on an async job with no output schema and no annotations, the description covers the full lifecycle (pause detection, resume, stop, terminal status). The remaining gap is the auth requirement and what session_id must reference.

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 only 50%, so the description must compensate. It clarifies continue's two outcomes ('fresh budget' vs 'work so far is kept') beyond the schema's own text, and ties job_id to the awaiting-decision state, but leaves session_id and authorization undocumented in both places.

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+resource (resume a paused async chat job awaiting a continue decision) and explicitly names the sibling it is not (approve_change). An agent can distinguish it from get_job, cancel_job, and approve_change without opening any schema.

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?

Gives an explicit trigger condition to poll get_job until status=awaiting_approval AND metadata.awaiting_kind='continue_prompt', then act. It also names the alternative endpoint (approve_change) and states the exclusion that this tool 'can only act on a continue-prompt pause'.

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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