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Search Mental Models

search_models

Search mental models by keyword across codes, names, and definitions to find relevant models for decision-making and problem-solving.

Instructions

Search HUMMBL mental models by keyword across codes, names, and definitions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (minimum 2 characters)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
resultCountYes
resultsYes
Behavior3/5

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

With no annotations, the description must disclose behavioral traits. It specifies the fields searched (codes, names, definitions) but does not mention whether the search is case-sensitive, returns partial matches, or handles pagination. It also does not state that it is read-only. The presence of an output schema partially offsets the lack of return format details.

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?

The description is a single sentence with no redundant words. It efficiently conveys the essential purpose and scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple single-parameter search tool with an output schema, the description is largely complete. It covers the action, resource, and search fields. However, it could mention additional context such as case-insensitivity or result ordering to prevent misuse.

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 covers the 'query' param with 100% coverage, but the description adds meaning by specifying which fields are searched (codes, names, definitions). This helps the agent understand the search scope beyond what the schema provides.

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 action (search by keyword), the resource (HUMMBL mental models), and the scope (across codes, names, and definitions). It differentiates from siblings like 'get_model' (specific model retrieval) and 'search_problem_patterns' (different entity).

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 explicit guidance on when to use this tool versus siblings such as 'search_problem_patterns', 'get_model', or 'list_all_models'. The description only implies usage for keyword-based search but fails to mention alternatives or exclusions.

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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