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autosearch_get_run_paper

Get the generated paper for a completed run. Returns markdown, JSON metadata, or PDF download URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNomarkdown
run_idYes

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It discloses return formats but lacks details on error behavior (e.g., if run_id is invalid or run not completed). It does not confirm read-only nature or side effects.

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 very concise with two sentences: one stating the purpose and one listing return types. Every word is necessary; no filler.

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?

Given the absence of output schema and annotations, the description provides the core functionality but lacks parameter explanations, error conditions, or usage context. It is adequate for a simple retrieval tool but could be more thorough.

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 should add meaning to parameters. It does not describe 'run_id' or 'format' beyond what the schema provides. The enum values for format are clear, but the description adds no extra context about valid values or usage.

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's function: 'Get the generated paper for a completed run' and specifies the return types (markdown, JSON metadata, PDF download URL). It differentiates itself from siblings like 'autosearch_get_run_status' which retrieves run status, not the paper.

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?

The description implies usage for completed runs, providing some guidance. However, it does not explicitly mention when not to use (e.g., if run is incomplete) or recommend alternatives like 'autosearch_get_run_status' to check completion status first.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool has a distinct and clearly separated purpose: launching, status checking, listing runs, retrieving papers, searching evidence, and verifying DOIs. No two tools overlap in functionality.

Naming Consistency5/5

All tools follow a consistent 'autosearch_verb_noun' pattern in snake_case, with verbs like get, list, run, search, verify. The prefix is uniform, making the set predictable.

Tool Count5/5

With 6 tools, the server is well-scoped. It covers the essential operations for AI research automation without being excessive or insufficient.

Completeness4/5

The tools cover the core workflow of launching, monitoring, retrieving results, and auxiliary searches. Missing operations like canceling or deleting runs, but the surface is largely complete for typical use.

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