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54yyyu
by 54yyyu

zotero_semantic_search

Find papers by semantic similarity to a topic query across your Zotero libraries using AI embeddings, without scanning abstracts.

Instructions

Prioritized topic-search tool. Find papers by semantic similarity to a query using AI embeddings — the BEST tool for finding papers on a topic (e.g. 'papers about mindfulness-based therapy'), far more efficient than scanning collection items or reading abstracts. Searches across every indexed library by default (your personal library plus any group libraries that have been synced); use library_id to scope to one. query: the topic or concept; natural-language phrases work well. limit: max results (default 10). filters: optional metadata filters as a dict (e.g. {'itemType': 'journalArticle', 'year': '2023'}); also accepts a JSON string. library_id: optional — restrict results to one library. 0 or 'user' for your personal library, or a group's numeric groupID (see zotero_list_libraries). Omit to search all indexed libraries. Requires the semantic search database to be POPULATED — run zotero_update_search_database first if you just installed the server or added new items; check readiness with zotero_get_search_database_status. Available only when the [semantic] optional dependency is installed. Example: zotero_semantic_search(query='mindfulness-based cognitive therapy for depression', limit=5).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (default: 10)
queryYesSearch query text - can be concepts, topics, or natural language descriptions
filtersNoOptional metadata filters as dict or JSON string. Example: {"item_type": "note"}
library_idNoOptional library scope — 0/"user" for the personal library, a groupID for a group library, or None (default) to search every indexed library.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It comprehensively discloses behavioral traits: searches across all indexed libraries by default, the ability to scope with library_id, the requirement for a populated database, the dependency on the [semantic] optional module, and the example usage. This is thorough and leaves no hidden behavior.

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-organized and front-loaded with the purpose. Every sentence adds value, but it is somewhat lengthy (about 150 words). It could be trimmed slightly without losing essential information, but overall it is efficient and structured.

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?

The description covers all necessary context: what the tool does, when to use it, prerequisites, parameter details, example usage, and availability. Given that the output schema is provided separately, the description does not need to explain return values. It is fully complete for an AI agent to select and invoke the tool correctly.

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?

Although the schema already describes all 4 parameters (100% coverage), the description adds substantial meaning: for query it notes natural-language phrases work well, for limit it repeats the default, for filters it clarifies it can accept a dict or JSON string and gives an example, and for library_id it explains the values '0' or 'user', references zotero_list_libraries, and clarifies that omitting it searches all libraries. This goes well 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 it is a 'Prioritized topic-search tool' that finds papers by semantic similarity. It explicitly distinguishes itself from scanning collections or reading abstracts, and provides a concrete example query. This leaves no ambiguity about the tool's specific purpose.

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?

The description explicitly specifies when to use this tool (for topic searches like 'papers about mindfulness-based therapy'), and contrasts it with less efficient alternatives. It also clearly explains the prerequisite: the semantic search database must be populated via zotero_update_search_database first, and references zotero_get_search_database_status for readiness checking. This provides excellent guidance.

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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