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tianmu

Perplexica MCP Server

by tianmu

search_reddit

Search Reddit discussions using AI. Get relevant results with sources and AI responses in readable text or JSON.

Instructions

Search Reddit discussions using Perplexica.

Args: query: The Reddit search query chat_provider: Chat model provider (optional, uses env config if not provided) chat_model: Specific chat model to use (optional, uses env config if not provided) optimization_mode: Speed vs quality tradeoff (optional, uses env config if not provided) output_format: Output format - "formatted" for human-readable text or "json" for raw JSON

Returns: Formatted text with AI response and sources, or JSON if output_format="json"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
chat_providerNo
chat_modelNo
optimization_modeNo
output_formatNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 disclosing behavior. It fails to mention rate limits, authentication requirements, error handling, or whether the operation is read-only or destructive. The output format is noted but core behavioral traits are absent.

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 structured with Args and Returns sections, making it easy to parse. It is mostly concise but includes redundant parameter explanations that mirror the schema. The first sentence is direct, but the overall length could be reduced.

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 the tool has 5 parameters (1 required) and no annotations, the description provides basic purpose and parameter semantics. It mentions the output format, and the presence of an output schema reduces the need to detail return values. However, it lacks usage context, examples, and limitations, leaving gaps for effective agent 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?

The description adds minimal meaning beyond the input schema by listing parameters in a docstring format, providing short explanations for each. However, schema coverage is 0% and the explanations are generic (e.g., 'optional, uses env config if not provided'), lacking specific constraints, examples, or default values.

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 searches Reddit discussions using Perplexica, with a specific verb (search) and resource (Reddit discussions). It distinguishes from sibling tools like search_web and search_youtube by specifying the target platform.

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 such as search_web or search_academic. There are no scenarios, exclusions, or criteria mentioned, leaving the agent without context for selection.

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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