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send_papers

Send research papers to your e-reader by arXiv ID, DOI, or title. Deduplicates references and skips already-sent papers.

Instructions

Send papers to the e-reader by arXiv id, DOI, or title.

refs accepts arXiv ids ('2401.12345', 'arXiv:...'), arXiv abs/pdf URLs, DOIs, doi.org URLs, and paper titles — the same ref values search and recommendation results carry. Publisher landing-page URLs are NOT resolvable — use the DOI or title. Version suffixes ('2401.12345v2') are ignored; the latest arXiv version is delivered. collections optionally files the papers into topical Zotero collections (created on demand) in addition to the Reading Queue — check list_collections and ask the user when placement is unclear.

Refs are deduplicated, and papers already tagged as sent in Zotero are skipped unless force=True. Large batches are split automatically to fit the 25-attachment / 50 MB per-email limits. dry_run=True previews what would be sent, with estimated sizes, without downloading or delivering — use it before big sends.

Papers without an open-access PDF are not sent; if Zotero is configured they are still queued (tagged no-oa-pdf) so they can be delivered manually later. Without Zotero there is NO cross-call duplicate protection — re-sending the same ref ships another copy. Relay the full receipt — sizes, skips, and failures — to the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refsYes
forceNo
dry_runNo
collectionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations exist, so the description carries full burden. It details deduplication, skipping already-sent papers, auto-splitting batches, handling of open-access PDFs, Zotero integration, and dry_run behavior. This is comprehensive for a mutation tool.

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?

The description is well-structured and front-loaded with the main purpose. Each sentence adds value, covering edge cases and behaviors. It could be slightly more concise, but it remains informative without unnecessary repetition.

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?

Given the tool's complexity (4 parameters, output schema exists), the description is complete. It covers input formats, behaviors, side effects, error handling, and expected output (receipt). The existing output schema obviates the need to describe return values.

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 0%, so the description fully compensates. It explains the accepted formats for refs, the effect of force, dry_run, and the optionality of collections. While it doesn't restate defaults, it adds practical context beyond 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?

The description clearly states the tool sends papers to an e-reader by arXiv id, DOI, or title. It uses specific verbs ('send') and resources ('papers'), and distinguishes from siblings like 'file_papers' and 'send_queue' which have different actions.

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?

The description provides guidance on when to use the tool, including using dry_run for previews, checking list_collections for placement, and noting limitations like no duplicate protection without Zotero. It lacks explicit 'when not to use' but the context is clear given sibling tools.

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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