Skip to main content
Glama

session_view_image

Retrieve an image from visual memory by its ID to obtain Base64 inline content for AI analysis. Check available image IDs using session_load_context.

Instructions

Retrieve an image from visual memory using its ID. Returns the image as Base64 inline content for the LLM to analyze. Use session_load_context first to see available image IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesProject identifier.
image_idYesThe short image ID (e.g., '8f2a1b3c') from the visual memory index.
Behavior4/5

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

Without annotations, the description discloses the return format (Base64 inline content) for LLM analysis, which is sufficient for understanding the tool's behavior, though no limits or side effects are mentioned.

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?

Two concise sentences with no wasted words, efficiently conveying purpose, output, and prerequisite.

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?

No output schema, but description explains return value; covers essentials for a simple retrieval tool with clear dependency hint.

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%, but the description adds example '8f2a1b3c' for image_id, clarifying it's a short ID from the memory index, adding value 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 retrieves an image by ID and returns it as Base64 inline content, distinguishing it from sibling tools that save or search memory.

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

Usage Guidelines4/5

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

It directs users to first use 'session_load_context' to see available image IDs, providing clear context for when to use this tool, though no explicit when-not criteria.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dcostenco/prism-coder'

If you have feedback or need assistance with the MCP directory API, please join our Discord server