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ShadovvSinger

Ollama_MCP_Guidance

simple_generate

Generate text from a prompt using any Ollama model. Provide the model name and prompt to receive a response with generated content and metadata.

Instructions

Basic text generation with Ollama models.

This is a simplified implementation of the /api/generate endpoint that provides
basic text generation capabilities without advanced features.

Limitations:
1. No streaming support
2. No raw mode
3. No format control
4. No parameter tuning (options)
5. No context management

Features:
1. Basic generation: Single prompt and response
2. Error handling: Connection and format validation
3. Performance metrics: Processing time and token statistics

Args:
    model (str): Model name to use, e.g., "llama2", "mistral"
    prompt (str): Text prompt for generation

Returns:
    str: JSON-formatted string containing:
        - Generated text and metadata if successful
        - Error details if the request fails

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
promptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description fully discloses limitations (no streaming, no raw mode, etc.), features (basic generation, error handling, performance metrics), and return format. This provides sufficient behavioral context for an agent.

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?

The description is well-structured with clear sections (limitations, features, args, returns) and front-loaded with the core purpose. It is somewhat verbose but each section adds value.

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 the simple tool (2 parameters, output schema exists), the description covers all necessary aspects: purpose, limitations, features, parameter explanations, and return format. It is fully sufficient for an agent to use correctly.

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?

The schema has 0% description coverage, but the description includes an 'Args' section that explains each parameter with examples ('llama2', 'mistral'), adding meaning beyond the schema's property names.

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 it is for 'basic text generation with Ollama models' and explicitly lists limitations and features, differentiating it from more advanced endpoints. However, it does not directly contrast with sibling tool 'simple_chat', which may cause ambiguity.

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

Usage Guidelines3/5

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

The description implies usage for simple generation without advanced features like streaming or parameter tuning, but it does not explicitly state when to use this tool versus alternatives like 'simple_chat' or 'post_generate_embeddings'.

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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