Astria-Index

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

No annotations are provided, so the description carries the full burden. It comprehensively discloses behavioral traits: persistence ('days or weeks later'), tracking scope ('goal, progress, and related memories'), storage semantics ('stored verbatim'), return format ('session ID e.g., s001'), error conditions ('Returns an error if description is empty'), and side effects (creates resumable state usable by named siblings).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Despite being multi-paragraph, every section earns its place. Information is front-loaded with the core purpose, followed by usage heuristics, constraints, and technical details. The structure uses clear headers ('Use this when:', 'Args:', 'Returns:') that improve scannability. No tautology or repetition of the tool name.

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

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

Given the tool's single parameter and simple schema, the description is exceptionally complete. It covers invocation triggers, prerequisites (checking `my_sessions`), parameter semantics, return value format, error states, and sibling tool relationships. Even though an output schema exists, the additional return value description provides necessary context about ID format and error handling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (only type: string provided), requiring the description to compensate fully. The 'Args:' section adds essential semantics: the purpose ('What you're working on'), persistence behavior ('stored verbatim'), consumption context ('used to restore context when resuming'), and quality guidelines ('Be specific enough that you'll understand the goal when you come back later'). Without this, the agent would lack critical usage context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Start') and resource ('working session') and clearly defines the unique value proposition ('cross-conversation continuity'). It effectively distinguishes from siblings like `resume_session` (continuing existing) and `end_session` (terminating) by emphasizing the creation of new persistent state.

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

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

Provides explicit positive conditions ('Use this when:') with concrete examples including exact syntax, negative conditions ('Do NOT start a session for quick, single-conversation tasks'), and explicit alternative workflow ('Call `my_sessions` first to check for existing sessions to resume'). This leaves no ambiguity about tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.