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Beever-AI

Beever Atlas

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get_recent_activity

List the most recent discussion facts from a channel, ordered newest first. Optionally filter by topic for time-bounded queries.

Instructions

List the most RECENT facts from one channel, newest first, optionally scoped to a topic. Call it for time-bounded "what happened lately" questions.

When to use: "what's been discussed in this channel this week", "what happened with topic X in the last N days". When NOT to use: search not bounded by recency (use search_channel_facts); a synthesized answer or reasoning across the items (use ask_channel).

Prerequisites: a channel_id from list_channels.

Returns (instant, read-only): {activity: [{text, author, timestamp, channel_id, topic_tags, fact_id}, ...]} sorted by timestamp descending. No side effects.

Error modes (returned as dicts): 'authentication_missing' (no principal); 'channel_access_denied' (token lacks access to channel_id). Other internal failures return an empty {activity: []}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channel_idYesChannel id. Get it from list_channels (e.g. 'ch-eng'). Required.
daysNoLook-back window in days, 1-90 (out-of-range values are clamped). Default 7.
topicNoOptional topic filter (e.g. 'deployment'); keeps only facts tagged with that topic. Omit for all topics. Default null.
limitNoMax activity items, 1-50 (out-of-range values are clamped). Default 20.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Discloses read-only, no side effects, return format, error modes, prerequisites, and clamping behavior. No annotations provided so description carries full burden.

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?

Well-structured with clear sections (When to use, When NOT to use, Prerequisites, Returns, Error modes). Front-loaded with main purpose, no wasted words.

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?

Complete for a read-only listing tool: explains return format, errors, prerequisites, parameter constraints. Output schema exists, so return description is sufficient.

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%. Description mentions defaults and clamping, but schema already provides similar detail. Baseline 3 is appropriate.

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 clearly states 'List the most RECENT facts from one channel' with specific verb and resource, and distinguishes from siblings in usage guidelines.

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?

Explicit when-to-use examples ('what's been discussed...') and when-not-to-use with alternative tool names (search_channel_facts, ask_channel).

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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