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check_ollama

Verifies that Ollama is running and the configured embedding or chat model is installed, ensuring readiness for smart search and symbol explanation.

Instructions

Check whether Ollama is running and the configured embedding/chat model is installed.

Read-only: yes. No side effects. Call before smart_search or explain_symbol if unsure about Ollama availability.

Returns: dict: {ollama_running: bool, model_installed: bool, model: str, error: str or None}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_rootNoProject root. Auto-detected if omitted. Ignored by this tool.
Behavior5/5

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

No annotations provided, but description fully discloses read-only nature, no side effects, and return value format with keys and types. No contradictions.

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?

Very concise: one sentence for purpose, one for usage guidance, and a structured return format. No wasted words.

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?

For a simple check tool with one optional parameter and documented return dictionary, the description is complete. No output schema needed as return is fully described.

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% and includes description that project_root is auto-detected and ignored. Description adds no further meaning beyond schema. Baseline 3 is appropriate.

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?

Description clearly states verb 'Check' and resource 'whether Ollama is running and the configured embedding/chat model is installed'. This distinguishes it from siblings which are code analysis tools, not external service checks.

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 advises calling 'before smart_search or explain_symbol if unsure about Ollama availability', providing clear usage context and prerequisites.

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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