Proving Lab

extract_citations

Use when you have a reading list rather than one source — a bibliography to build, a set of links to verify before submitting, an archive to describe. Measured on 20 mixed sources: 10 became complete records in 8.1 s, 0.4 s each; the other 10 came back named rather than silently empty. Up to 50 addresses, five fetched in parallel. Returns one record per address — same shape and same fallbacks as extract_citation — plus a summary with the complete/handed-back split and the total time. Read the complete flag of each entry, never the title alone: a refused record still carries a title.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`urls`	Yes	Addresses to read, at most 50

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description carries full weight. It discloses performance metrics, the 50-address limit, parallel fetching of 5, the return shape with a summary, and critically warns that refused records still carry titles, requiring the `complete` flag check. This is exemplary transparency.

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?

Every sentence earns its place: triggering usage, performance benchmarks, limits/parallelism, return shape, and a critical caveat about the `complete` flag. The progression is logical and there is no fluff.

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?

For a single-parameter tool with no annotations and no output schema, the description covers the return format, summary contents, operational limits, and the essential flag-checking behavior. It also links to extract_citation for shape context. This is more than sufficient for correct usage.

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%, so the parameter is already documented as 'Addresses to read, at most 50'. The description repeats the limit and adds behavioral details (parallel fetching) but no new semantic meaning about the parameter itself, matching the baseline for high schema coverage.

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 clearly states the tool is for multi-source reading lists, contrasting with the single-source sibling extract_citation, and explicitly notes it returns one record per address. The use cases (bibliography, links to verify, archive) reinforce a specific verb+resource scope.

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?

It opens with 'Use when you have a reading list rather than one source' and provides concrete scenarios. The reference to extract_citation as the singular equivalent implies the alternative, giving clear when-to-use and when-not-to-use guidance.

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

All Proving Lab tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, such as single vs batch citation extraction. The only potential confusion is between list_measurements and get_measurement_data, both of which return measurement data; however, their descriptions indicate one lists available data and the other retrieves a specific figure's backing data.

Naming Consistency4/5

Tool names predominantly follow a verb_noun pattern (extract_citation, install_extension, list_measurements). Two exceptions—adoption_stats and how_to_capture—deviate from this pattern, but they are still readable and not chaotic.

Tool Count5/5

Ten tools is a reasonable scope for a specialized server covering citation extraction, measurements, capture guidance, and project status. No tool is redundant, and the count is neither too sparse nor overwhelming.

Completeness4/5

The server covers the main workflows: single/batch citation extraction, retrieving and listing measurement data, fetching reproducible methods, and obtaining capture setup instructions. Minor gaps exist, such as no tool for creating new measurements, but the domain is primarily read-only and contribution is handled through open_work.

Resources

Need Help?