opentweet_update_evergreen_settings

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

Annotations include idempotentHint=true and destructiveHint=true, already signaling that updates are idempotent and may modify existing state. The description adds basic behavioral context (what settings are controlled) but does not elaborate on side effects, permissions required, or implications of changes (e.g., disabling queue). Bar lowered by annotations leads to a score of 3.

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 efficient sentence listing the controllable aspects. It is front-loaded and avoids extraneous words. While concise, it could be slightly more structured with bullet points, but the current form is acceptable.

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 lack of required parameters and output schema, the description provides adequate context on what the tool modifies. However, it omits details about return values (e.g., success status or updated configuration), prerequisites, and effect timing (immediate vs. queued). This leaves some gaps for a complete understanding.

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 100%, with each parameter (enabled, posting_times, posts_per_day, default_cooldown_days) having clear descriptions in the input schema. The description reiterates these concepts but adds no new semantic meaning beyond summarizing them. Baseline 3 applies as schema already does the heavy lifting.

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 tool name 'opentweet_update_evergreen_settings' and description clearly state it updates evergreen queue settings. Specific verb 'Update' and resource 'evergreen queue settings' with explicit fields (active, posts per day, posting times, cooldown). Distinguishes from sibling tools like 'get_evergreen_settings' and 'add_to_evergreen' by focusing on settings modification.

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. It implies usage via 'Control whether the queue is active' but lacks directives like 'for reading settings use get_evergreen_settings'. Sibling tools exist for related actions but no comparative guidance is provided.

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