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arquimedes_search_problems

Read-onlyIdempotent

Search over 1 million competition and olympiad math problems by keyword, theorem, or LaTeX, filtering by category, competition, and difficulty. Use it to find matching problems before fetching answers and solutions by id.

Instructions

Find problems by keyword in 1,038,963 competition and olympiad math problems. Full-text search returns problems whose statement or title contains all the query words: a topic, a theorem name such as 'Cauchy-Schwarz', or a LaTeX fragment. Optional filters narrow by category, dataset, competition, and Mohs difficulty (1.0 to 10.0). Results are summaries (id, title, competition, year, difficulty, answer, statement) without solutions; pass an id to arquimedes_get_problem for solutions and hints. To get random problems instead of keyword matches, use arquimedes_sample_problems.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of problems to return (1-50, default 10).
queryYesSearch keywords, theorem name (e.g. 'Cauchy-Schwarz', 'pigeonhole'), or LaTeX snippet.
datasetNoOptional source dataset slug filter.
categoryNoOptional subject category filter.
max_mohsNoMaximum Mohs difficulty rating (1.0 to 10.0).
min_mohsNoMinimum Mohs difficulty rating (1.0 = elementary, 5.0 = AIME, 8.5+ = IMO/Putnam).
competitionNoOptional competition name (e.g. 'IMO', 'USAMO', 'AIME I', 'AMC 12A', 'HMMT February', 'Putnam').

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, so the bar is lower, and the description adds valuable context: results are summaries only (id, title, competition, year, difficulty, answer, statement) with no solutions, and an id must be passed to arquimedes_get_problem for solutions/hints. It does not mention pagination or rate limits, keeping it short of a 5.

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?

Three tightly packed sentences with no filler; scope and query semantics are front-loaded, followed by output shape and sibling routing. Every clause carries actionable information.

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

Completeness5/5

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

With no output schema, the description compensates by describing the returned fields and their limits (no solutions). For a 7-parameter read-only search tool, everything an agent needs to invoke it and follow up correctly is present.

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 coverage is 100%, so baseline is 3, but the description adds semantic detail the schema lacks: the query matches all words, accepts theorem names like 'Cauchy-Schwarz' or LaTeX fragments, and the Mohs range maps to levels (1.0 elementary, 5.0 AIME, 8.5+ IMO/Putnam). Filter names are largely repeated from the schema.

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?

States a specific verb (find/search) and resource (competition and olympiad math problems), plus corpus size. It explicitly differentiates from siblings by naming arquimedes_get_problem for solutions and arquimedes_sample_problems for random retrieval, so an agent can route without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly defines the query semantics (returns problems whose statement or title contains ALL query words) and names the alternative tool for the random-use case. The condition selecting each sibling is stated, leaving little to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.