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memory_recall

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Follow links across a knowledge graph to answer relational questions that single-shot search cannot chain, returning seeds, paths, entities, and supporting texts.

Instructions

Multi-hop retrieval over the knowledge graph, for RELATIONAL questions whose answer is reached by following links — "what does X ultimately run on?", "how does A reach C?" — which single-shot memory_search can't chain. Read-only. low_confidence: true means no seed entity matched — fall back to memory_search.

Returns: {seeds, entities, edges, paths, texts, iterations}. entities/edges/texts are capped with a per-hop reservation, so a hub seed's own 1-hop ring can't crowd out the deeper hops the walk exists to reach; edges prefers links between surviving entities; each entity's facts is capped too. A fact carrying re_verify stands on a memory that has since been corrected — the value still stands, but check it before acting. A seed entity's constraint facts come first, marked pinned. truncated: true (with searches_issued) means a search ceiling or time budget stopped the walk early: some re-queries, and possibly deeper hops, were skipped, so supporting texts and deeper entities may be missing — narrow the question or lower hops. Details: docs/guide/retrieval.md.

Input Schema

Name	Required	Description
`hops`	No	Max graph hops. Clamped to 1..5.
`query`	Yes	Natural-language relational question; its top hits seed the graph walk.
`top_k`	No	Positive integer. Bounds only the SEED search (the initial hits that name the walk's start entities), not the result, which is capped separately; up to 3 ``texts`` slots go to seed hits.
`verbose`	No	Full fact/edge provenance and untruncated texts. Default facts are ``{attribute, value}``, edges ``{src, relation, dst}``, texts truncated to a preview.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.18.1Oct 14, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

changedInput schema / properties / top_k / description

Previous value: -"Bounds only the SEED search (the initial hits that name the walk's start entities), not the result, which is capped separately; up to 3 ``texts`` slots go to seed hits."New value: +"Positive integer. Bounds only the SEED search (the initial hits that name the walk's start entities), not the result, which is capped separately; up to 3 ``texts`` slots go to seed hits."

addedInput schema / properties / top_k / minimum
```
Added value: +1
```

Changed4 schema fields changedv0.15.0Sep 3, 2026

addedInput schema / properties / hops / description

Added value: +"Max graph hops. Clamped to 1..5."

addedInput schema / properties / query / description

Added value: +"Natural-language relational question; its top hits seed the graph walk."

addedInput schema / properties / top_k / description

Added value: +"Bounds only the SEED search (the initial hits that name the walk's start entities), not the result, which is capped separately; up to 3 ``texts`` slots go to seed hits."

addedInput schema / properties / verbose / description

Added value: +"Full fact/edge provenance and untruncated texts. Default facts are ``{attribute, value}``, edges ``{src, relation, dst}``, texts truncated to a preview."

First observedv0.11.0Jul 31, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations only cover the safety profile (readOnly, non-destructive); the description goes well beyond by disclosing the capping/reservation behavior, the meaning of re_verify (memory corrected, value still stands but check it), pinned constraint facts, and the truncated/searches_issued early-stop semantics with remediation advice.

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

Conciseness4/5

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

Purpose and the memory_search distinction are front-loaded, and each subsequent sentence describes a distinct return-field behavior (caps, re_verify, pinned, truncated). It is dense and long, but almost every sentence earns its place by adding behavioral semantics rather than restating structured fields.

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

Completeness5/5

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

An output schema exists, yet the description supplies the interpretation layer the schema can't (what truncation and re_verify mean for the caller). For a multi-hop, non-idempotent retrieval tool, an agent has everything needed to call it correctly and interpret results.

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 coverage is 100%, so hops, query, top_k, and verbose are already fully documented in the schema, establishing a baseline of 3. The description adds only marginal param meaning, e.g. tying hops to truncation ('lower hops') and hinting at question narrowing, but adds no syntax 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?

States a specific verb+resource ('Multi-hop retrieval over the knowledge graph') and scopes it to RELATIONAL questions with concrete examples. It explicitly distinguishes itself from the sibling memory_search by noting single-shot retrieval 'can't chain' the links this tool follows.

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?

Gives explicit when-to-use ('what does X ultimately run on?'), when-not (single-shot questions belong to memory_search), and a concrete fallback condition (low_confidence: true means no seed matched, fall back to memory_search). Nothing is left to inference.

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