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find_tool

Read-onlyIdempotent

Find the right tool for any network action: search by query (e.g., 'create a VLAN') using semantic and keyword matching, then use the returned name to invoke read or write tools.

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, normalized capability, curated/generated origin, and exact OpenAPI operation-ID 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. origin: Filter by curated or generated implementation. operation_id: Filter by an exact generated OpenAPI operationId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
originNo
serverNo
platformNo
capabilityNo
operation_idNo
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, idempotentHint, destructiveHint), the description reveals deduplication, match annotation types, safety flag mirroring, and compact default results. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear opening, usage note, result details, and parameter list. Some redundancy could be trimmed, but overall effective and front-loaded.

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 tool's complexity (8 parameters, output schema), the description covers all essential aspects: usage, filters, defaults, and integration with sibling tools. Output schema exists so return values need not be explained.

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 tool description provides detailed explanations for all 8 parameters in the Args section, adding significant meaning beyond the 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 finds tools by query using semantic search and keyword matching. It distinguishes itself from sibling tools like 'search_docs' and 'invoke_tool' by being the discovery step.

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 says 'Call this first when you need an action.' Provides actionable guidance on how to use the returned name with invoke_read_tool or invoke_tool, and when to set include_schema=True.

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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