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search_activities

Find relevant past work by searching activity titles and content with hybrid keyword and semantic matching, optionally filtering by tag, time, or source.

Instructions

Hybrid search over activity titles and content, combining keyword (FTS5) and semantic similarity. This is the default search tool — it handles both concrete phrases like 'retry strategy' and loosely-worded queries, so prefer it unless you specifically need pure vector similarity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
tagNoFilter matches by enrichment tag (e.g. bugfix, decision, incident)
limitNo
queryYesKeywords to search for in titles and content
startNo
sourceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.23
    • addedInput schema / properties / tag
      Added value: +{
+  "description": "Filter matches by enrichment tag (e.g. bugfix, decision, incident)",
+  "type": "string"
+}
  2. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses the hybrid matching mechanism (FTS5 keyword plus semantic similarity) and the breadth of query handling, which is useful behavioral context. It does not detail result ranking or pagination, but the core search behavior is transparently described.

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 sentences with no filler. The mechanism is front-loaded, followed by a decision rule. Every sentence contributes useful information for tool selection.

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?

Given six parameters, low schema coverage, no annotations, and no output schema, the description is not complete enough. It provides strong orientation but leaves optional-filter semantics and return-value expectations underspecified.

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

Parameters2/5

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

Schema description coverage is only 33%, and the description does not compensate. It clarifies the query semantics implicitly but does not explain start, end, limit, or source meaning or format. The agent is left to guess for four of six parameters.

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 states a specific verb and resource: 'Hybrid search over activity titles and content'. It further distinguishes itself from the sibling semantic_search_activities by declaring that this is the default tool unless pure vector similarity is needed.

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?

It gives an explicit usage rule: prefer this tool by default, and provides a clear when-not condition: use it unless you specifically need pure vector similarity. It also notes the tool handles both concrete and loosely-worded queries, helping an agent choose correctly.

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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