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AiAkiv Memory

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find_memories_by_entity

Read-onlyIdempotent

Look up entities by name and return the events they appear in.

Use this when the user names a person, project, system, or term and wants
what is recorded about it. Do not use it for an open question about a topic;
use `search_memory` for that.

Read-only. Scope is decided by the server and reported in `searched_scope`.

Args:
    entity_name: Substring to match, case-insensitive. May be empty when
        `entity_id` is given.
    entity_id: Exact entity id (`ent_...`), for following an entity a
        previous response named. Same scope as a name lookup; it takes
        precedence over `entity_name`.
    limit: Max events per entity (1-50, clamped).

Returns:
    `{query_name, hint, suggestion, matches, tag_matches, searched_scope}`.
    The same substring also matches tags, which arrive in `tag_matches`.
    Each match's `top_partners` is the co-occurrence ranking across the whole
    scope, which is what "which entity co-occurs most with X?" asks for;
    `hint.entities[].hit_count` counts only within this response's sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax events per entity (1-50, clamped).
entity_idNoExact entity id (`ent_...`), for following an entity a previous response named. Same scope as a name lookup; it takes precedence over `entity_name`.
entity_nameNoSubstring to match, case-insensitive. May be empty when `entity_id` is given.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive safety, so the description adds value by disclosing that scope is server-decided and reported in `searched_scope`, that the substring also matches tags, and that `top_partners` is a whole-scope ranking while `hit_count` is sample-limited. 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.

Conciseness4/5

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

The description is well-structured with purpose, usage, Args, and Returns sections, and front-loads the most important guidance. The Args section is redundant with the schema, but the Returns clarification earns its place.

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?

For a read-only lookup with three fully documented parameters and an output schema, the description covers when to use it, scope behavior, tag matching, and the meaning of ranking fields. Nothing needed for correct invocation is missing.

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 the schema already documents all three parameters. The description's Args section largely repeats those descriptions and adds no new parameter-level meaning, though it does reinforce precedence and case-insensitivity.

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 opens with a specific verb and resource ('Look up entities by name and return the events they appear in') and immediately distinguishes itself from search_memory. This makes the tool's role clear among a large sibling set.

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 trigger condition ('when the user names a person, project, system, or term'), an explicit exclusion ('Do not use it for an open question about a topic'), and names the alternative (`search_memory`). It also explains when `entity_id` should be used, which is strong routing guidance.

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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