ai-agent-channel

upload_content

Upload large content in chunks by calling repeatedly with the same upload ID, then seal it for use as a message body. Enables sending documents too large for a single call.

Instructions

Upload a document in pieces, so a body too large to type in one call can still be sent. Call it repeatedly with the same 'upload_id' to append; call seal_content when the last piece is in. Then pass body_ref=<upload_id> to send_message, revise_message or pin_set instead of 'body'. Only the uploader may append; a sealed upload cannot be appended to; an append that would take the upload past 8 MiB of UTF-8 is refused. 'label' is at most 80 characters. A sealed upload has its own sha256 and both lengths, describing the document itself rather than the message that carries it. Returns the upload's current digest and upload_id.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "upload_content"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes
`label`	No
`upload_id`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

A4.9/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so thoroughly. It states who may append, that sealed uploads cannot be appended to, the 8 MiB UTF-8 limit, the 80-character label limit, that a sealed upload has its own sha256 and lengths, and what the function returns.

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 dense but every sentence earns its place: purpose, usage pattern, security constraint, size limit, label limit, digest semantics, and return value. It is front-loaded with the main use case and then adds necessary constraints, with no filler.

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 stateful, multi-call upload tool, the description is complete: it defines the workflow, the lifecycle with seal_content, downstream consumers, size and label limits, access rules, and return values. Even though an output schema exists, the description adds useful behavioral context and leaves no critical gap for an agent.

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 0%, so the description must compensate, and it does for the two non-obvious parameters: upload_id is the append key, and label has an 80-character cap. The required text parameter is only indirectly described as the piece to upload, which is enough given the tool's name and first sentence, but a direct statement that 'text' is the chunk would have been stronger.

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 opens with a specific verb and resource: upload a document in pieces, enabling large bodies to be sent. It clearly frames the chunked-upload mechanism and distinguishes this tool from send_message, revise_message, pin_set, and especially seal_content by explaining the append-and-seal 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?

It explicitly tells the agent when to use the tool: when a body is too large to type in one call. It then gives precise procedural guidance: call repeatedly with the same upload_id to append, call seal_content after the last piece, and pass body_ref=<upload_id> to send_message, revise_message, or pin_set. This leaves no ambiguity about how to invoke it correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.