Skip to main content
Glama

akai_layer

Inspect ONNX model layers and extract specific components with layer-aware precision.

Instructions

akai-layer — Layer-aware ONNX model inspection and extraction (C port). (category: knowledge)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoCLI arguments to pass to the operator
stdinNoOptional stdin data
Behavior2/5

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

No annotations provided; description does not disclose whether operations are read-only or destructive. 'Extraction' could imply modification, but it's ambiguous.

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?

Single sentence with category tag; front-loaded with name, minimal waste. Could be slightly more informative without losing conciseness.

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?

Lacks explanation of output, usage patterns, or how parameters combine. For a tool with two optional params and no output schema, more detail is needed.

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?

Schema coverage is 100% with clear parameter descriptions. Description adds context about CLI usage and C port, but does not significantly enhance meaning beyond schema.

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?

Description clearly states it performs ONNX model inspection and extraction with layer awareness, but does not differentiate from siblings like akai_model or akai_query.

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?

No guidance on when to use this tool versus alternatives. The description only states what it does without context on prerequisites or exclusions.

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/aurekai/aurekai-mcp'

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