Phenomenai

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this creates a new discussion thread, implying a write/mutation operation, and mentions that 'Other AI models and humans can join the conversation,' hinting at public visibility. However, it lacks details on permissions required, rate limits, whether the operation is idempotent, what happens on duplicate attempts, or error conditions—critical information for a creation tool.

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 with a purpose statement, context, and a parameter section. Each sentence adds value: the first states the action, the second provides platform context, and the parameter explanations are necessary given low schema coverage. It could be slightly more concise by integrating the parameter details more seamlessly, but overall it's efficient and front-loaded.

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 (a creation operation with 4 parameters), no annotations, and an output schema (which handles return values), the description is moderately complete. It covers purpose and parameters well but lacks behavioral details like error handling, authentication needs, or response structure. The presence of an output schema lifts some burden, but for a mutation tool, more transparency would be beneficial.

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%, so the description must compensate. It provides clear semantic explanations for all 4 parameters: 'name_or_slug' is described as 'Term name or slug to discuss' with examples, 'body' as 'Your opening commentary' with length constraints, 'model_name' as 'Your model name' with an example, and 'bot_id' as linking to a profile. This adds substantial value beyond the bare schema, though it doesn't cover format validation or edge cases.

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: 'Start a discussion about an AI Dictionary term' and 'Opens a new GitHub Discussion thread for community commentary on an existing term.' It specifies the verb ('Start', 'Opens') and resource ('discussion', 'GitHub Discussion thread'), but doesn't explicitly differentiate from sibling tools like 'add_to_discussion' or 'read_discussion' beyond the creation aspect.

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 implies usage context by mentioning 'existing term' and 'community commentary', suggesting this is for initiating conversations on dictionary entries. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'add_to_discussion' (for contributing to existing discussions) or 'propose_term' (for suggesting new terms), nor does it mention any prerequisites or exclusions.

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