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quant-rag

quant-rag

by Elias-outofsample
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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timeline

Build a year-by-year chronology of a research topic, highlighting the key passage from each document to trace idea evolution and separate foundational works from recent preprints.

Instructions

Chronologie d'un sujet : le meilleur passage de chaque document, groupé par année de publication.

Utile pour voir comment une idée a évolué (rough volatility 2014 → 2026) ou pour distinguer les travaux fondateurs des preprints récents.

Args: topic: le sujet, formulé comme une question ou un intitulé. year_min: borne basse (inclus). year_max: borne haute (inclus). limit: nombre de documents (défaut 20).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic": "<topic>"
    },
    "name": "timeline"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
topicYes
year_maxNo
year_minNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does so well: it reveals the core behavior (one best passage per document, year grouping, inclusive year bounds, limit default) and the intended analytical use. It does not explain the meaning of null year bounds or the criterion for 'best passage', but these are minor given the read-only, query-like nature of the tool.

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 compact and well structured: a one-sentence definition, a short usage rationale, then a clean Args list. It is front-loaded with the most important behavior and contains no redundant sentences.

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?

An output schema exists, so the description does not need to document return values. Combined with the Args list and usage rationale, an agent has enough to call the tool correctly. The remaining gaps are the behavior of null year bounds and the exact meaning of 'best passage', but these are not blocking for basic invocation.

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?

Schema description coverage is 0%, so the Args section is the only source of parameter meaning. It adds helpful semantics for every parameter: topic should be phrased as a question/title, year_min/year_max are inclusive bounds, limit defaults to 20. The phrase 'nombre de documents' is slightly ambiguous (total vs per year), preventing a 5.

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 opening sentence states exactly what the tool does: it builds a chronology of a topic by taking the best passage from each document and grouping those passages by publication year. This is a specific, informative description that immediately distinguishes timeline from siblings like search_documents or list_documents. It is not a tautology of the tool name.

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 second paragraph explicitly identifies when timeline is useful: observing how an idea evolves or separating foundational works from recent preprints. It gives a concrete example (rough volatility 2014→2026). It does not explicitly name alternatives or state when not to use them, so it falls short of full routing guidance.

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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