recordari

why_connected

Read-only

Find direct connections between two memories, in either direction. Prefer from_id/to_id when you already have exact ids — resolution is exact-match and errors if a given id has no matching live memory, rather than silently falling back to label search. This is the recommended way to verify an exact pair (e.g. before connect(relationship=resolved)). Use from_label/to_label when you only have a concept in mind, not an id — resolution is a fuzzy substring match against the most recently created candidate. Each side resolves independently, so from_id may be combined with to_label.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`to_id`	No
`domain`	No
`from_id`	No
`to_label`	No
`from_label`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedAug 31, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavioral detail: id resolution errors when no live memory matches, label resolution falls back to fuzzy substring matching against the most recently created candidate, and there is no silent fallback from id to label. No contradiction with annotations.

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?

Every sentence adds distinct value: core purpose, exact-id guidance with error behavior, recommended use case, label fallback semantics, and independent resolution. The description is front-loaded with the action and uses clear contrasts without redundancy.

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 read-only tool with no output schema, the description covers the main resolution modes and error behavior well. The missing explanation of the domain parameter is the main gap, and the description does not state what happens if neither ids nor labels are supplied. Otherwise, an agent has enough to call it correctly.

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 description coverage is 0%, so the description carries the burden. It thoroughly explains from_id, to_id, from_label, and to_label, including resolution modes and combinability. The domain parameter, however, is never mentioned, leaving a five-parameter tool with one parameter unexplained.

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?

Description opens with a specific verb and resource: 'Find direct connections between two memories, in either direction.' It clearly distinguishes this tool from siblings like connect, recall, and suggest_connections by framing it as a verification/query tool for exact pairs, even naming connect as a follow-up use case.

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?

Explicitly specifies when to use from_id/to_id versus from_label/to_label, explains the exact-match versus fuzzy-match behavior, and gives a concrete recommended scenario: 'before connect(relationship=resolved)'. It also states that sides resolve independently, so mixed id/label combinations are allowed.

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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TDQS

A4.2/5.0

Disambiguation4/5

Each tool targets a distinct operation—lifecycle (remember/revise/forget), graph edges (connect/disconnect/why_connected), retrieval (recall/search/recent/history/orient/significance)—and the descriptions carefully disambiguate overlaps. However, the read/analysis cluster (recent, history, orient.recent, significance) could still cause initial misselection before reading the detailed descriptions.

Naming Consistency3/5

Names are readable and consistently lowercase, but they do not follow a single convention: most are bare verbs (connect, remember, revise, search, visualise) while others are nouns (domains, history, recent, significance) and two are multiword phrases (suggest_connections, why_connected). This mix is still predictable enough to navigate, but less coherent than a uniform verb_noun surface.

Tool Count4/5

16 tools is slightly above the typical 3–15 band, but the scope of a knowledge-graph memory server justifies the breadth: CRUD, connections, domain admin, and multiple query/analysis tools are all represented. No tool feels redundant enough to cut, though the set is at the heavy end.

Completeness4/5

Core lifecycle is well covered: create/read/update/archive/purge, connection creation/removal, domain admin, and multiple query/analysis modes. The main gap is that bulk domain merge (merge_domains) is referenced in tool descriptions but not exposed as an MCP tool, so agents must direct users to an external admin interface for that operation.

Resources

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