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space0

by space.0
OverviewDiscussionsAdmin

Upload an image or sticker for a post

ingest_post_media

Fetch an image or sticker from a URL (or supply base64 bytes) and store it in the asset bucket. Returns {ok, asset_key, url, width, height} - pass asset_key + url to create_memory_post content.asset_key / content.url. kind=image for photos/illustrations; kind=sticker for transparent PNG/WEBP overlays. source_url must be https and public; bytes_base64 is the alternative for local data. Exactly one of source_url or bytes_base64 is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesimage or sticker binding.
spaceYesSpace slug to associate this upload with.
widthNoImage width hint in pixels (skips header probe if provided alongside height).
heightNoImage height hint in pixels (skips header probe if provided alongside width).
source_urlNoHTTPS URL to fetch the media from.
bytes_base64NoBase64-encoded raw bytes (alternative to source_url).
content_typeNoMIME type (required when using bytes_base64; image/png, image/jpeg, image/webp, image/gif for image; image/png or image/webp for sticker).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / height / maximum
      Removed value: -9007199254740991
    • removedInput schema / properties / width / maximum
      Removed value: -9007199254740991
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations (readOnlyHint: false, openWorldHint: false) are limited. The description adds significant behavioral context: it stores in asset bucket, returns specific fields, and imposes constraints (source_url must be https and public, MIME types for sticker).

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?

Description is well-structured and front-loaded with the main action. Every sentence adds value, though slightly lengthy; still efficient.

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?

Given 7 parameters, no output schema, and complexity, the description fully covers inputs, constraints, and output. It even explains how to use the output with a sibling tool, making it highly complete.

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 baseline is 3. The description adds value by explaining the mutual exclusivity of source_url and bytes_base64, MIME type requirements, and the purpose of kind. It also details output fields beyond schema.

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 fetches an image or sticker from a URL or base64 and stores it, distinguishing it from sibling tools like create_memory_post which use the output.

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 explains when to use source_url vs bytes_base64, that exactly one is required, and how to pass the output to create_memory_post. Provides clear alternatives and usage context.

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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