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

No annotations are provided, so the description carries the full burden. It discloses that the tool pulls engagement metrics (likes/comments/views/shares/follower delta) for posts in the launch run and returns per-account analytics, top posts, best-time-to-post, and a structured next-move recommendation. This provides good insight into its behavior, though it doesn't mention authorization or rate limits.

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 front-loads the alias and use condition. It is informative and contains no fluff, but could be slightly more structured (e.g., breaking into when/inputs/outputs). However, it remains concise and effective for an AI agent.

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?

With 4 parameters and no output schema, the description explains the return values (per-account analytics, top posts, best-time-to-post, next-move recommendation) and covers inputs and usage context. It is complete enough for an agent to understand what the tool produces and how to invoke it properly.

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% for all 4 parameters, each with adequate descriptions. The tool description adds value by explaining that runId comes from chiefmo_launch_product, accountIds defaults to all accounts in the launch, outputMode has two choices with default behavior, and lookbackDays defaults to 7 with max 90. This contextualizes the parameters beyond the 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: it performs a post-launch review by pulling 24h+ engagement metrics and recommending next steps. It distinguishes itself by specifying when to use (≥24h after chiefmo_publish_approved_post) and what it returns (analytics + recommendation). This aligns with a specific verb+resource: 'post_launch_review' and sets it apart from sibling tools like chieflab_suggest_next_move.

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 explicitly states when to use the tool: 'USE WHEN ≥24h has passed since chiefmo_publish_approved_post fired and the user asks...' This provides clear usage context. It does not explicitly mention when not to use or alternatives, but the condition '≥24h' implies it should not be used earlier. This is sufficient for guidance.

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