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Resume Context

resume_context
Read-onlyIdempotent

Packages a stored context handoff block into a destination-ready bundle to resume an AI conversation on another platform.

Instructions

Packages a stored ContextBridge handoff block into a destination-ready landing bundle for resuming the conversation on another AI platform.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesThe destination platform: claude, chatgpt, or gemini.
context_blockYesThe structured ContextBridge handoff block to resume from.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesThe destination AI platform.
handoff_kindYesIdentifies this as a destination-side resume package.
resume_readyYesWhether the package is ready to use immediately.
format_versionYesSchema version for resume context output.
operator_stepsYesStep-by-step instructions for using this handoff package.
continuation_planYesThe intended first move after the receiving AI loads the handoff.
api_resume_payloadYesThe split system/user payload to use when the destination supports separate instruction channels.
usage_instructionsYesA concise explanation of how to use this resume package.
manual_resume_messageYesThe single paste-ready message to use when the destination only supports a single opening message.
prompt_structure_notesYesNotes explaining why this landing package is structured this way.
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is clear. The description adds context about the packaging process and destination readiness, which is useful but does not introduce new behavioral traits beyond what annotations imply.

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 a single, complete sentence with no wasted words. It is front-loaded with the action verb 'Packages' and conveys the core purpose efficiently.

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 complexity of the input (2 required parameters, one deeply nested with 12+ subfields), the description is concise but adequate. The presence of annotations and an output schema (not shown) reduces the burden. However, a brief note about what a 'ContextBridge handoff block' is could improve completeness for unfamiliar agents.

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

Parameters3/5

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

Schema coverage is 100% with detailed descriptions for each parameter (target enum with platforms, context_block with nested structure). The description does not add meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 verb 'Packages', the resource 'stored ContextBridge handoff block', and the result 'destination-ready landing bundle for resuming the conversation on another AI platform'. It distinguishes from siblings like compress_context and format_for_target by focusing on resuming, not compressing or formatting.

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?

The description implies usage for resuming conversations across platforms but does not explicitly state when to use this tool versus alternatives (e.g., compress_context, format_for_target). No 'when not to use' or comparison guidance is provided.

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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