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Enhanced Knowledge Graph Memory Server

search_nodes_ranked

Find relevant nodes in a knowledge graph using TF-IDF ranking to prioritize search results based on query relevance and importance filters.

Instructions

Perform TF-IDF ranked search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query
tagsNo
minImportanceNo
maxImportanceNo
limitNoMax results
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'TF-IDF ranked' which hints at ranking behavior, but doesn't disclose critical traits like whether it's read-only, performance expectations, error handling, or output format. For a search tool with no annotations, this is insufficient behavioral context.

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, efficient phrase with zero waste. It's appropriately sized and front-loaded, making it easy to parse quickly without unnecessary elaboration.

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

Completeness2/5

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

Given 5 parameters with low schema coverage (40%), no annotations, no output schema, and complexity from sibling tools, the description is incomplete. It lacks details on behavior, parameter usage, and differentiation from alternatives, making it inadequate for effective tool selection and invocation.

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 description coverage is 40% (only 'query' and 'limit' have descriptions), and the description adds no parameter details beyond the schema. It doesn't explain what 'tags', 'minImportance', or 'maxImportance' do or how they affect TF-IDF ranking. With low coverage, the description fails to compensate, resulting in minimal added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Perform TF-IDF ranked search' states a specific action (search) and algorithm (TF-IDF ranked), but it's vague about what resource is being searched (nodes vs. other entities) and doesn't clearly distinguish from sibling tools like 'search_nodes', 'boolean_search', 'fuzzy_search', or 'semantic_search'. It provides a technical method but lacks clarity on scope.

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 guidance is provided on when to use this tool versus alternatives. With many sibling search tools (e.g., 'search_nodes', 'boolean_search', 'semantic_search'), the description fails to indicate appropriate contexts, exclusions, or comparisons, leaving the agent without usage direction.

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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