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search_entries

Search stored knowledge entries using FTS5 full-text queries or vector similarity, then filter by type, tags, project, purpose, and archive status to find relevant records.

Instructions

Search entries with FTS5 and filters

Input Schema

NameRequiredDescriptionDefault
tagsNo
typeNoFilter by entry type
limitNoMax results (default 10)
queryNoSearch query
vectorNoUse vector/cosine similarity search instead of FTS5
projectNoFilter by project
purposeNoFilter by purpose (WORK|KNOWLEDGE|LEARNING|RELATIONSHIP|STATE)
include_archivedNoInclude archived entries

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden and it does not. It names the search engine (FTS5) but says nothing about ranking, result shape, whether archived entries are excluded by default (implied only via the include_archived param name), cost of vector search, or pagination/limits behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One short clause with no wasted words, but it is under-specified rather than concise. The scarce space is spent on an implementation detail (FTS5) instead of disambiguation or default behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An 8-parameter, zero-required search tool with no annotations and no output schema needs far more than one clause: default matching mode, tag filter semantics (AND/OR), archived handling, and return format are all absent. The complexity of the tool is not matched by the description.

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

Parameters3/5

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

Schema description coverage is 88%, so most parameters are self-documenting and baseline 3 applies. The description's only added semantic is that FTS5 is the default mode and the vector parameter switches engines, which is modest value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a verb (search) and resource (entries) plus the mechanism (FTS5 with filters), which is more than tautology. But it never distinguishes itself from siblings like search_by_tags, vault_mem_search, or search_links, all of which also search entries by different means, so an agent cannot tell when this is the right search tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance at all. The description does not explain relationship to search_by_tags (tag-only search) or vault_mem_search, nor does it say when to prefer FTS5 keyword matching versus the vector flag it exposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.