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Lune Research

by com.luneresearch
OverviewDiscussionsAdmin

List conferences

list_conferences
Read-onlyIdempotent

Use this when the user asks “what conferences does Lune track”, “is venue X covered”, or wants a category-level browse (e.g. AI/ML, security, databases, software/systems). Pass category as a keyword (ai, security, ...) to narrow; it matches the conference's research area.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_conferences"
  }
}

Input Schema

NameRequiredDescriptionDefault
categoryNoOptional research-area filter, matched case-insensitively against the conference's field. Accepts short codes (`ai`, `ml`, `nlp`, `cv`, `security`, `databases`, `software`, `systems`) or any substring of the field name. Omit to list every conference.

Output Schema

NameRequiredDescriptionDefault
conferencesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds only that the filter matches a conference's research area, and says nothing about catalog size, pagination, or coverage gaps.

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?

Effectively two sentences, front-loaded with the use case before the parameter tip. The quoted example queries are slightly verbose but each supports recognition of the trigger.

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

Completeness4/5

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

With an output schema present, a single fully documented optional parameter, and complete annotations, the description only needs to supply usage intent, which it does. It is a bit thin on what the listing returns (names, categories, coverage), but that is largely covered by the output schema.

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 coverage is 100% and the schema itself lists the short codes and substring matching rules in detail. The description's note that `category` matches the conference's research area is essentially a restatement, so baseline 3 applies.

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

Purpose4/5

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

The description makes clear this lists the conferences tracked by Lune and supports a category-level browse, with examples of the research areas involved. It doesn't explicitly contrast with siblings like get_conference_papers, which retrieves papers for a single venue, so an agent must infer that boundary.

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?

Strong trigger guidance is given via quoted user phrasings ('what conferences does Lune track', 'is venue X covered') and the category-browse case. It explains how to narrow with `category`, but names no alternative tools or when-not-to-use conditions.

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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