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RikaiDev

yomi

Official
by RikaiDev

get_insight

Analyzes message patterns to surface conversations where a reply is overdue, with previews for quick triage.

Instructions

A compact "what needs my attention" context network over the local index — you make the final call, this assembles the evidence cheaply. Nodes: connectors (people across ≥2 of your chats, with structural bridges) and relationships (per-conversation engagement, reply rhythm, recency). open: conversations whose latest message is NOT yours, ranked by how overdue they are relative to your usual reply rhythm there, each with fromName (last speaker), a preview of the latest message, overdueRatio/typicality, and a lastMessageId pointer. It carries NO message threads and makes NO judgement about addressee, nicknames, or open-request vs closing-ack — those are language understanding you do by reading each preview (a group message may be addressed to someone else, who then owns it), fetching the full thread with get_chat_messages only for the few worth it. Reads across all conversations (denylist-excluded dropped). Empty only when the index is empty.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chatIdNoOptional focus: restrict `relationships` and `pending` to this chat (as returned by list_conversations). Omit to scan all conversations.
sinceHoursNoLookback window in hours, measured back from the newest captured message (not wall-clock). Default 504 (21 days).
Behavior5/5

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

Discloses that it carries no message threads, makes no judgement about addressee, reads across all conversations, and returns empty only when index empty. Fully transparent given no 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?

Dense but efficient: every sentence provides value, front-loaded with purpose. No redundancy.

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?

Explains output structure, parameters, edge cases (empty index, denylist). Complete without output schema.

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 has 100% coverage with descriptions, but description adds context: chatId is optional, sinceHours default is 504. Adds practical meaning beyond 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?

Clearly states it assembles a 'what needs my attention' context network, describing nodes and 'open' conversations. Distinguishes from siblings by noting it carries no message threads and leaves judgement to the user.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context on when to use ('get compact evidence') and suggests following up with get_chat_messages for full threads. Implicitly excludes use for fetching threads, but no explicit alternatives or when-not-to-use.

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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