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vystartasv

Works With Agents MCP Server

by vystartasv

wwa_facts_query

Retrieve structured facts—paths, project structures, preferences—from the shared agent knowledge base to answer queries without re-asking users or searching blindly.

Instructions

Query the shared agent knowledge base. Facts are structured environment truths — Python paths, project structures, preferences, deployment targets. Agents discover facts without re-asking users or searching blindly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 20, max 100)
entityNoWhat the fact is about (e.g. 'python', 'spfx', 'works-with-agents'). Omit to search all.
categoryNoFact category: env, preference, project, reference, user_fact, auth
attributeNoProperty name (e.g. 'path', 'version', 'domain'). Omit to search all.
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 for behavioral disclosure. It only states 'Query' and what facts are, but does not mention that the tool is read-only, how results are returned, pagination behavior, or any side effects. The description adds context about content but not about the tool's operational behavior.

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 exactly two sentences: the first states the action and resource, the second gives essential context on what facts are. No redundant or filler content.

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?

The tool is simple (4 optional params, no output schema), but the description does not explain what the query returns (e.g., a list of matching facts) or how filters combine. It is adequate for understanding the core purpose but incomplete for an agent to fully anticipate the tool's output without additional inference.

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 already covers all parameters with descriptions (100% coverage), but the description enriches the meaning by giving examples like 'Python paths, project structures, preferences, deployment targets', which help agents map the 'entity' and 'category' parameters to concrete values. This goes beyond the schema's generic descriptions.

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 uses the specific verb 'Query' with a clear resource ('shared agent knowledge base') and defines what facts are ('structured environment truths'), which distinguishes it from sibling tools like wwa_facts_list_categories or wwa_skills_search. It is not a tautology and gives concrete examples of fact content.

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?

The description provides clear context for when to use the tool: 'Agents discover facts without re-asking users or searching blindly.' This implies the tool is for retrieving known environment truths. However, it does not explicitly name alternatives or explain when not to use it, such as when listing categories is more appropriate.

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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