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Beever-AI

Beever Atlas

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start_new_session

Begin a new conversation session by generating a unique session ID, discarding previous context to start a clean thread for unrelated topics or explicit reset requests.

Instructions

Mint a fresh conversation session id that starts a new ask_channel thread.

Call this to begin a clean conversation that carries no memory of prior ask_channel turns — e.g. when the user switches to an unrelated topic or explicitly asks to "start over" / "forget previous context". Pass the returned id as the session_id argument on subsequent ask_channel calls so they share one continuous thread; reuse the same id for follow-ups, and mint a new one only when you want a clean break.

When NOT to use: do not call this before every question. ask_channel auto-creates a session when session_id is omitted, so a new session id is only needed to intentionally drop earlier conversation context.

Prerequisites: none. Requires an authenticated MCP principal (the caller's connection token); no channel_id or other input is needed.

Returns: a dict {"session_id": "mcp:<principal>:<short>"} where the value is a fresh opaque conversation handle scoped to the caller, e.g. {"session_id": "mcp:conn_abc123:9f3c1a2b"}. On a missing or invalid principal it returns {"error": "authentication_missing"} instead.

Side effects: none — this allocates a new conversation boundary marker and does not delete, persist, or mutate any stored data. Latency: instant (no network or LLM call); safe to call synchronously inline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Describes side effects (none), latency (instant), safety (safe synchronous call), return format with example, and error case. Since no annotations are present, the description fully handles behavioral disclosure.

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: purpose first, then usage, prerequisites, returns, side effects. Every sentence adds unique value; no redundant or filler content.

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 no params and presence of output schema (context signal), description covers all needed context: purpose, usage conditions, prerequisites, return value with example and error, side effects. Complements sibling tool ask_channel effectively.

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?

No parameters exist in input schema, so schema coverage is 100%. With 0 parameters, the baseline is 4; description adds no param info but provides return value semantics as a bonus.

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?

Starts with verb 'Mint' and resource 'fresh conversation session id', clearly stating the action and output. Distinguishes from sibling tool 'ask_channel' by explaining it starts a new thread for a clean break.

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?

Explicitly specifies when to use (unrelated topic, start over) and when NOT to use (before every question, noting auto-creation by ask_channel). Prerequisites and authentication requirement are stated.

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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