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Pubroot

by io.github.buildngrowsv
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Search Pubroot papers

search_papers
Read-onlyIdempotent

Search papers published on Pubroot by keyword (title and abstract), category (journal/topic), minimum review score, badge or status. Returns metadata and abstracts, sorted by review score.

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": "search_papers"
  }
}

Input Schema

NameRequiredDescriptionDefault
badgeNoFilter by badge ('verified_open', 'verified_private', 'text_only').
limitNoMaximum number of results (1-50).
queryNoKeyword search (matches title and abstract). Empty string returns all papers.
statusNoPaper status filter ('current', 'superseded', 'expired'). Empty string matches any status.current
categoryNoFilter by category in journal/topic format (e.g. 'ai/llm-benchmarks').
min_scoreNoMinimum review score to include (0.0 to 10.0).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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 value beyond that by disclosing the return content ('metadata and abstracts') and the result ordering ('sorted by review score'), though it says nothing about pagination, result counts, or how the limit interacts with total matches.

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?

A single sentence that front-loads the search scope before listing filters and the return shape; there is no filler. It is dense but readable, with only a small cost in that the filter list and return behavior are packed into one clause chain.

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 no output schema, the description carries the burden of explaining return values and does so briefly (metadata plus abstracts, score-ordered), and all parameters are optional and documented in the schema. Remaining gaps are minor: no mention of pagination, empty-result behavior, or how many results to expect against the limit.

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 description coverage is 100%, so every one of the six parameters is already documented, including enum-like values for badge and status and the journal/topic format for category. The description largely restates those filters rather than adding new semantics, so the baseline of 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 names a specific verb and resource ('Search papers published on Pubroot') and enumerates the filterable dimensions (keyword, category, min review score, badge, status), which is enough to distinguish it from single-paper retrieval tools like get_paper. It stops short of explicitly contrasting itself with any sibling.

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

Usage Guidelines3/5

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

Usage is only implied: the filter list suggests 'use this when you want to find a set of papers matching criteria'. There is no statement of when to prefer this over get_paper or get_related_work, and no guidance on what to do when zero results are returned or how filter combinations interact.

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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