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WebRTCGame

SQLite Project Memory MCP

by WebRTCGame

resolve_entity_by_name

Find existing project entities by name in the SQLite Project Memory database to identify tasks, metadata, and relationships for AI agents managing complex project states.

Instructions

Resolve a human-readable name to an existing entity when possible.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
entity_typeNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It hints at a lookup operation ('resolve') but lacks details on permissions, rate limits, error handling, or what 'when possible' means (e.g., partial matches, case sensitivity). This is inadequate for a tool with 3 parameters and no annotation coverage.

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 sentence with no wasted words. It's front-loaded and appropriately sized for its content, though it could benefit from more detail given the tool's complexity.

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

Completeness3/5

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

Given 3 parameters with 0% schema coverage, no annotations, and an output schema (which reduces need to explain returns), the description is incomplete. It covers the basic purpose but lacks usage, behavioral, and parameter details needed 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.

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain 'name' (e.g., format, uniqueness), 'entity_type' (e.g., allowed values, null handling), or 'limit' (e.g., pagination, default behavior). This leaves all 3 parameters poorly documented.

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 states the tool's purpose as resolving a human-readable name to an existing entity, which is clear but vague. It specifies the action ('resolve') and target ('entity'), but doesn't differentiate from siblings like 'get_entity' or 'search_content', nor does it explain what 'resolve' entails (e.g., lookup, validation, or retrieval).

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions 'when possible' but doesn't specify conditions, prerequisites, or exclusions, and offers no comparison to sibling tools like 'get_entity' or 'find_similar_entities' for similar tasks.

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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