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create-session

Start a reasoning session to incrementally build knowledge bases for multiple queries, with automatic expiration after a set time period.

Instructions

Create a new reasoning session for incremental knowledge base construction.

When to use: You want to build up premises incrementally and query multiple times. When NOT to use: Single query with all premises known upfront (use prove directly).

Example: ttl_minutes: 30 → Returns: { session_id: "uuid...", expires_at: ... }

Notes:

  • Sessions auto-expire after TTL (default: 30 minutes)

  • Maximum 1000 concurrent sessions

  • Session ID must be passed to all session operations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ttl_minutesNoSession time-to-live in minutes (default: 30, max: 1440)
verbosityNoResponse verbosity: 'minimal' (token-efficient), 'standard' (default), 'detailed' (debug info)
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: sessions auto-expire after TTL (with a default), there's a maximum of 1000 concurrent sessions, and the session ID must be passed to all session operations. However, it lacks details on error handling or performance limits beyond concurrency.

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-structured with clear sections (purpose, usage guidelines, example, notes), each sentence adds value without redundancy, and it's front-loaded with the core purpose. It efficiently conveys necessary information in a compact format.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (creating sessions with expiration and concurrency limits), no annotations, and no output schema, the description does a good job covering key aspects like purpose, usage, behavioral traits, and an example. However, it could be more complete by detailing the output structure beyond the example or error scenarios.

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 description coverage is 100%, so the schema already documents both parameters (ttl_minutes and verbosity) thoroughly. The description adds minimal parameter semantics beyond the schema, such as implying ttl_minutes affects expiration in the example, but it doesn't provide additional syntax or format details. This meets the baseline of 3 when schema coverage is high.

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's purpose as 'Create a new reasoning session for incremental knowledge base construction,' which is a specific verb ('Create') + resource ('reasoning session') with clear scope ('incremental knowledge base construction'). It distinguishes from sibling tools like 'prove' by emphasizing incremental building versus single-query operations.

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?

The description includes explicit 'When to use' and 'When NOT to use' sections, clearly stating to use this tool for incremental premise building and querying multiple times, and to avoid it for single queries with known premises (using 'prove' instead). This provides direct guidance on alternatives and context.

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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