qllm_heavy_discuss

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

Annotations indicate non-destructive, non-read-only, open world. Description adds that the tool may write reports and HTML files (if write_report set), and that host_mode can return a prompt instead of running (codex mode). These are important behavioral details beyond the annotations.

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 a single paragraph that covers purpose, args, and returns. It is concise and front-loaded with the main action. Could be slightly more structured but not overly verbose.

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 complexity with many parameters and nested schema, the description adequately explains the overall concept and returns. It mentions key options like host mode and report writing. The output schema exists to detail return values. Minor gap: does not explain the two host modes in detail.

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?

The input schema (HeavyDiscussInput) contains detailed descriptions for all parameters. The description provides a high-level summary but adds little new meaning beyond what the schema already offers. The summary is useful but not essential.

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 runs a HeavySkill-style multi-perspective discussion across providers. It specifies the action (run), method (multi-perspective discussion), and scope (across providers). This distinguishes it from siblings like qllm_chat or qllm_compare.

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?

The description does not explicitly state when to use this tool versus alternatives. Usage is implied by the complexity of the discussion, but no direct guidance on when not to use or conditions for choosing over siblings like qllm_pipeline.

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