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Upload User Profile Image

upload_user_profile_image

Upload a user profile image by providing the user ID and base64 encoded image data to update their account picture.

Instructions

Upload a profile image for a user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesBase64 encoded file data
userIdYesUser ID
Behavior2/5

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. It states the action ('upload') but doesn't describe what happens during execution: whether it overwrites existing images, requires specific permissions, has rate limits, returns a confirmation or error details, or affects other user data. For a mutation tool with zero annotation coverage, this lack of behavioral context is a significant gap.

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, efficient sentence with zero wasted words. It front-loads the core action ('upload') and target ('profile image for a user'), making it immediately scannable. Every word earns its place, and there's no redundancy or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address key contextual aspects: what the tool returns (e.g., success status, image URL), error conditions (e.g., invalid user ID, malformed image), or side effects (e.g., whether it triggers notifications). The agent lacks sufficient information to understand the full impact of invoking this tool.

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?

The input schema has 100% description coverage, with clear documentation for both parameters ('userId' and 'image' as base64 encoded data). The description adds no additional parameter semantics beyond what's in the schema, such as image format requirements (e.g., JPEG/PNG) or user ID validation rules. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema already provides adequate parameter information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('upload') and resource ('profile image for a user'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'upload_staging_site_file' by specifying the target resource as a user profile image rather than a staging site file. However, it doesn't explicitly differentiate from other user-related tools like 'update_user' or 'create_user', which could potentially handle profile images indirectly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., user must exist), constraints (e.g., image format/size limits), or relationships with sibling tools like 'update_user' that might also modify user data. The agent must infer usage from the tool name alone, which is insufficient for optimal selection.

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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