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reply_chunk

Stream reply chunks progressively to the operator, appending text in real time. Set done:true on the final chunk to close the turn.

Instructions

Stream a reply progressively to the operator instead of sending it all at once. Pass the same chat_id as reply and call this multiple times — each call broadcasts a chunk to the operator's dashboard live (they see text growing in real time). The FINAL call must set done: true to close the turn. Use this whenever your reply is long, when you're narrating progress through a multi-step task, or when generating output that builds up over time (file synthesis, code, multi-paragraph explanations). For short atomic replies, use reply instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doneYestrue on the final chunk; closes the turn, persists the consolidated text, dispatches to route originators. false on intermediate chunks.
textYesThe chunk to append. Empty allowed (e.g. final empty chunk solely to mark done).
chat_idYesSame chat_id as the inbound prompt — every chunk in a turn shares it.
Behavior5/5

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

Given no annotations, the description fully discloses the streaming behavior: each call broadcasts a chunk live, the final call must set `done: true` to close the turn, and the consolidated text is persisted. No contradictions with any missing annotations.

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 approximately six sentences, front-loaded with purpose, then immediately provides usage guidance, protocol details, and a sibling reference. Every sentence is informative with no wasted words.

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 streaming tool with 3 parameters, no output schema, and no annotations, this description covers purpose, when to use, behavioral protocol, parameter semantics, and interaction pattern. It is fully self-contained and leaves no critical gaps.

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 parameters are already described. The description adds value by explaining the role of `done` in closing the turn, that `text` is appended incrementally, and that `chat_id` must be shared across chunks. This goes beyond the schema definitions.

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 tool streams a reply progressively, distinguishing it from the sibling `reply` which sends all at once. It specifies the verb 'stream' and resource 'reply', making the purpose unambiguous.

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 states when to use this tool ('when your reply is long, when you're narrating progress...') and when to use the alternative ('For short atomic replies, use `reply` instead'). Also describes the required protocol for marking the final chunk with `done: true`.

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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