luopan_chat

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

With no annotations, the description fully discloses behavior: backend-enforced limits, return fields with meanings, and lifecycle management. It clearly states what happens when limits are hit, meeting the full burden for behavioral transparency.

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?

The description is well-structured: purpose statement, runtime constraints, structured return fields, and actionable usage notes. Each sentence earns its place; no redundancy.

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 output schema not provided as structured input, the description enumerates return fields and their meanings. It fully explains the session lifecycle, restrictions, and expected behavior, providing complete context for an AI to use the tool correctly within the sibling ecosystem.

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 coverage is 0%, so description must add meaning. It explains session_id comes from prior luopan_analyze, and question provides usage tips ('specific events/years/topics yield better answers'). This adds significant value beyond the bare schema.

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 clearly states the tool's purpose: 'Ask a follow-up question against an existing chart-reading session.' It specifies the resource (session) and verb (ask), and distinguishes from sibling tool luopan_analyze, which starts new sessions.

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?

Explicitly guides when to use (follow-up questions) and when not to (session expired or followup_remaining==0, then call luopan_analyze). It also details constraints (2-hour TTL, 5-question cap) and gives actionable advice (warn user when remaining==1).

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