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Beever Atlas

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search_channel_facts

Search a known channel for specific facts using hybrid BM25+vector retrieval. Returns ranked, cited facts without synthesized reasoning.

Instructions

Find SPECIFIC facts in ONE channel by hybrid (BM25 + vector) search and return them as raw, ranked rows. Call it when you want the cited source facts themselves, not a composed answer.

When to use: targeted lookup of facts in a known channel ("find facts about the postgres migration"). Faster and more precise than ask_channel for retrieval-only tasks.

When NOT to use: you need a synthesized answer with reasoning (use ask_channel); you don't know which channel holds the facts (use search_memory, which fans this same search across every accessible channel); you want a deterministic substring match rather than ranked relevance (use find_facts).

Prerequisites: a channel_id from list_channels.

Returns (instant, read-only): {facts: [{text, author, timestamp, permalink, channel_id, confidence, topic_tags}, ...]}. No side effects.

Error modes (returned as dicts): 'authentication_missing' (no principal); 'channel_access_denied' (token lacks access to channel_id). On any other internal failure it returns an empty {facts: []} rather than erroring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channel_idYesChannel id to search. Get it from list_channels (e.g. 'ch-eng'). Required.
queryYesSearch query, keyword or natural phrase (e.g. 'postgres migration'). Matched with BM25+vector hybrid retrieval. Required.
time_scopeNoTime window. 'any' = all facts (default), 'recent' = last 30 days only.any
limitNoMax facts to return, 1-50 (values outside the range are clamped). Default 10.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations exist, so the description fully carries the burden. It discloses read-only nature, no side effects, return structure, error modes (authentication, access denial), and that internal failures return empty facts rather than erroring. Complete transparency.

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 well-organized into distinct sections (purpose, when/not to use, prerequisites, returns, error modes). Every sentence adds value; no redundancy or fluff. Ideal length for an actionable tool description.

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?

Given the output schema exists, the description correctly limits return value explanation to a sample structure. Covers prerequisites, error handling, and behavioral nuances. Completely addresses the tool's complexity.

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 baseline is 3. The description adds minimal parameter semantics beyond the schema (e.g., restates channel_id from list_channels). No additional constraints or format details. Adequate but not exceptional.

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 explicitly states the tool finds 'SPECIFIC facts in ONE channel by hybrid (BM25 + vector) search' and returns raw ranked rows. It clearly distinguishes from siblings like ask_channel and search_memory by scope and output type.

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?

Provides clear when-to-use ('targeted lookup of facts in a known channel') and when-not-to-use for synthesized answers (ask_channel), unknown channels (search_memory), or substring match (find_facts). Explicitly lists alternatives.

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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