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Search typed memory links

search_typed_links
Read-onlyIdempotent

Searches stored graph-style links from memory facts and conversation turns to find connections between people, jobs, PRs, receipts, files, tools, and decisions.

Instructions

Searches stored graph-style links extracted from Memory facts and conversation turns. Use this when a worker needs to find connections between people, jobs, PRs, receipts, files, tools, and decisions. Prefer search_memory for broad recall and search_typed_links for relationship lookups.

Input Schema

NameRequiredDescriptionDefault
queryYesLink search query
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.5

TDQS

A4.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful context about the source of the links and the relationship-focused behavior, but it does not describe result format, matching behavior, or limits beyond what the schema provides.

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?

The description is three tight sentences with no filler. The core purpose is front-loaded, followed by usage context and the key alternative tool.

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 simple two-parameter search tool with rich annotations and no output schema, the description gives enough context to select and invoke the tool correctly. The main remaining gap is that it does not clarify result shape or the role of max_results.

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 50%, and the description does not explain max_results at all. The entity examples indirectly help clarify what the query parameter is for, but the description does not compensate for the undocumented parameter coverage.

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 uses a specific verb and resource: it searches stored graph-style links extracted from Memory facts and conversation turns. It also clearly distinguishes this from broad memory recall by naming search_memory as the alternative.

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 explicitly states when to use this tool: when a worker needs connections between people, jobs, PRs, receipts, files, tools, and decisions. It also directly contrasts it with search_memory, saying to prefer search_memory for broad recall and this tool for relationship lookups.

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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