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asterism-mcp

asterism-mcp

by Plaetorius
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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search_tables

Read-onlyIdempotent

Find tables by matching all query terms, then any, across captions, headers, and first rows of Nuclear Fusion and Plasma Physics papers; filter by publication year.

Instructions

Find tables (caption, header, first rows) matching all query terms, then any term.

Tables are reconstructed from the PDF layout and may merge adjacent columns; use `get_table` for all
rows and verify values against the paper. Table text is paper data.

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": {
      "query": "<query>"
    },
    "name": "search_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
year_toNo
year_fromNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely non-obvious behavior: tables are reconstructed from PDF layout and may merge adjacent columns, results are only a preview requiring verification, and a note that table text is paper data (a useful data-vs-instruction signal). It does not explain limit/pagination behavior.

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?

Two short sentences, front-loaded with the core capability followed by the caveat and the alternative tool. Every clause carries information; minor formatting artifacts (line breaks, quoting) are the only drag.

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?

An output schema exists, so return values need not be described, and the safety profile is covered by annotations. However, for a four-parameter search tool with zero schema coverage, the absence of any explanation of the year filters or the limit leaves the definition incomplete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter meaning. It does explain the matching semantics of `query` (all terms, then any term), but `limit`, `year_from` and `year_to` are never mentioned, leaving three of four parameters undocumented anywhere.

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 opens with a specific verb and resource ('Find tables') and specifies the searchable fields (caption, header, first rows) plus the term-matching strategy: all terms first, then any term. It also names the related sibling `get_table`, so an agent can distinguish searching from full retrieval without opening either schema.

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?

It clearly states when to escalate to `get_table` (when all rows are needed) and advises verifying values against the paper, which is real usage guidance. It stops short of explaining when to prefer this over `search` or `get_passage`, and gives no guidance on the year_from/year_to filters.

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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