pyp6xer_lookahead

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

Annotations already provide read-only, non-destructive, idempotent hints. The description adds value by detailing the exact filtering logic (finish >= data_date, start <= data_date + days_ahead) and clarifying that it covers in-progress and future-starting activities. This exceeds minimal disclosure.

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 extremely concise, using two sentences that front-load the purpose and then specify the inclusion criteria. Every word earns its place; no unnecessary information.

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 simple filtering nature of the tool, the description fully explains the behavior. The presence of a separate output schema means return values are already documented. No additional context is needed for this specific tool.

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 100% with well-described parameters. The description does not add new semantic information beyond what the schema already provides for cache_key, days_ahead, and proj_id. It implicitly confirms the role of days_ahead in the logic but does not enhance parameter understanding.

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 with a specific verb ('Return') and resource ('activities') and provides a precise selection criterion based on a lookahead window. It distinguishes itself from sibling tools like list_activities (which likely returns all activities) by narrowing the scope to a specific time range.

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 for time-window queries but does not explicitly state when to prefer this tool over alternatives such as list_activities or search_activities. No 'use when' or 'use instead' guidance is provided, leaving the agent to infer context from the name and logic.

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