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find_tool

Read-onlyIdempotent

Find network automation tools by describing what you want to do. Combines semantic search with keyword matching to return tool names, filtered by platform or capability.

Instructions

Find tools by query. Combines semantic search + tool-name keyword match.

Call this first when you need an action. The returned name is what you pass to invoke_read_tool for read-only tools or invoke_tool for writes. Results are deduplicated; semantic matches are annotated match='semantic', name-overlap matches match='keyword', and safety flags mirror backend ToolAnnotations. Results are compact by default; set include_schema=True only when you need the full JSON schema for a selected tool. Optional platform, server, and normalized capability filters apply to both keyword and semantic matches.

Args: query: What you want to do. e.g. "create a VLAN", "disconnect a client". top_k: 1-10 results (default 5). include_schema: Include full JSON schemas in results. Defaults to False to keep MCP responses compact. platform: Filter by normalized platform, such as central, glp, mist, clearpass, or apstra. server: Filter by exact backend server name, such as aruba-monitoring. capability: Filter by read, diagnostic, write, or destructive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
serverNo
platformNo
capabilityNo
include_schemaNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), description adds deduplication behavior, match annotation types, safety flag mirroring, and default compactness of results.

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?

Well-structured with a brief overview and an Args section; each sentence adds value. Slightly verbose but for a complex tool it is appropriate.

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?

Complete coverage given the tool's complexity (6 parameters, output schema exists). Addresses usage, behavior, parameters, and output details without relying on output schema for explanation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description fully explains all 6 parameters: query with examples, top_k default, include_schema condition, and filters (platform, server, capability).

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?

Clearly states 'Find tools by query' and 'Combines semantic search + tool-name keyword match', distinguishing from siblings like find_device, find_client, search_docs.

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?

Explicitly says 'Call this first when you need an action' and explains how to use the returned `name` with invoke_read_tool or invoke_tool. Does not explicitly exclude alternatives but context is adequate.

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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