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Eclipse-Cj

Paper Distill MCP Server

add_topic

Add a research topic by providing a key, label, and keywords to enable targeted paper searches.

Instructions

Add a research topic for paper search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesShort identifier (e.g. "llm-reasoning", "rag-retrieval"), lowercase with hyphens
labelYesHuman-readable name (e.g. "LLM Reasoning")
weightNoPriority weight 0.0-1.0 (default 1.0 = highest priority)
keywordsYesSearch keywords for this topic (3-5 recommended)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

Without annotations, the description bears full responsibility for disclosing behavioral traits. It only states 'Add a research topic' without explaining side effects (e.g., persistence, overwrite behavior, idempotency) or whether the operation requires prior initialization.

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 a single, succinct sentence that immediately conveys the tool's purpose. It is front-loaded and efficient, though it could benefit from additional details without becoming verbose.

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?

Despite having an output schema (not provided in this view), the description does not mention return values or behavior. For a tool with 4 parameters (3 required), the description is too sparse to be considered complete, especially given the lack of annotations.

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 input schema has 100% parameter description coverage, so the description adds no additional semantic value. The baseline of 3 is appropriate as the schema already documents each parameter adequately.

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 'Add a research topic for paper search' clearly states the action (add) and the resource (research topic), along with context (for paper search). This effectively distinguishes it from sibling tools like 'manage_topics' which likely handles broader topic management.

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 'manage_topics' or 'init_session'. It does not mention any prerequisites, limitations, or scenarios where this tool is appropriate or inappropriate.

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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