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

The annotations already declare a safe read operation (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds genuinely useful behavior an agent could not infer: interactive-client rendering as a clickable chart, the unit convention that retention positions are in seconds when video length is known, and that results include the same post on other platforms side by side plus a median-post comparison.

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?

It is well front-loaded, leading with the single-post scope before enumerating metrics, and the closing sentences carry actionable constraints (id sources, interactive rendering, seconds unit). The middle metric enumeration is long and dense as one run-on sentence, which costs some readability, but almost every clause carries 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?

There is no output schema, so the description carries full responsibility for explaining return values, and it does so thoroughly across video metrics, retention curve, cross-platform duplication, and median comparison. For a two-parameter read tool with full annotation coverage, an agent has everything needed to call it and interpret the result.

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%, so both postId and profileId are already documented, including the note that profileId is usually unnecessary. The description adds nothing parameter-specific beyond restating that post ids come from get_top_posts or get_post_history, so the baseline of 3 applies.

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 opens with a specific verb and resource, 'Everything about ONE published post', then enumerates the exact metric families returned (views, likes, comments, shares, watch time, retention curve, traffic sources) and adds cross-platform comparison. It is clearly distinguishable from get_analytics, get_top_posts, and get_post_history because it is scoped to a single post's diagnostics.

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?

It gives an explicit use case, 'explain why a post worked or fell short and what to change in the next edit', with a concrete example output, and tells the agent where to obtain the required postId from get_top_posts or get_post_history. It stops short of naming when an agent should prefer a sibling tool, such as aggregate get_analytics, so exclusions are left implicit.

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