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junnnnnw00

Obsidian Everywhere

by junnnnnw00

Semantic Search

semantic_search
Read-onlyIdempotent

Search notes by meaning, not just keywords. Finds conceptually related notes using embedding similarity, even when exact words don't match.

Instructions

Meaning-based search via embedding similarity (multilingual-e5-small) -- finds conceptually related notes even when they don't share the query's exact words, unlike search_notes' full-text matching. Lazily computes/caches embeddings on first use (up to 50 notes per call); if the vault isn't fully embedded yet, the response says how many notes remain and results may be incomplete until a later call finishes indexing them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 10).
queryYesFree-text search query.
folderNoOptional vault-relative folder scope.
Behavior5/5

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

Beyond annotations (readOnly, idempotent), it reveals lazy embedding computation, caching, a limit of 50 notes per call, and that incomplete indexing affects results—critical behavioral details.

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?

Two concise, front-loaded sentences with zero redundancy. Every sentence adds distinct value: purpose, differentiation, and behavioral quirks.

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?

Covers purpose, differentiation, and key behaviors. Lacks detail on return format (e.g., list of note paths), but the description explains the partial indexing signal.

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 covers 100% of parameters with descriptions. The description adds context on the limit's maximum and the incomplete results warning, providing extra value 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 'meaning-based search via embedding similarity' and explicitly contrasts with sibling tool 'search_notes' full-text matching, making the purpose and distinction unmistakable.

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 contrasts with search_notes, implying use for conceptual searches, and warns about incomplete results if not fully indexed. However, it lacks explicit '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.

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