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ask_library

Answer questions by searching your personal PDF library. Receive synthesized answers with citations from the source papers.

Instructions

Answer a question using the user's indexed PDF library via PaperQA2.

Searches the pre-built index (see index_library_pdfs()) and returns
a synthesised answer with citations from the source papers.

Args:
    question: Natural language question to answer from the library.
    top_k: Number of source passages to retrieve before synthesis (default 5).
    scope: Which index to query. "default" = full library. "ph_library" = PH background only.
           Build the index first with index_library_pdfs(scope=<scope>).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes
top_kNo
scopeNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided. The description discloses that it returns a synthesized answer with citations and uses PaperQA2, but does not detail potential behaviors like rate limits, error handling, or the synthesis process. It provides moderate transparency.

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 compact: two introductory sentences plus a structured Args block. Each sentence adds value. Could be slightly more concise, but overall efficient.

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?

For a Q&A tool with three parameters, the description covers the core functionality, parameter purposes, and prerequisite (building index). The presence of an output schema (not shown) reduces the need to describe return values. Minor missing context like error handling.

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

Parameters5/5

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

Schema coverage is 0%, but the description adds detailed semantics for all three parameters: question (natural language query), top_k (number of passages with default), and scope (options and prerequisite). This fully compensates for missing schema descriptions.

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 answers questions using indexed PDFs via PaperQA2. It specifies the resource (indexed PDF library) and action (synthesized answer with citations), distinguishing it from sibling tools like search_library which may return raw passages.

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 explains that the tool searches a pre-built index and references index_library_pdfs() for building it. It provides scope options and default values. However, it does not explicitly state when to avoid this tool or mention alternatives like search_library.

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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