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

Annotations only declare non-read-only, non-destructive, open-world; the description adds real behavior — liked=true hits the platform like endpoint and persists, liked=false unlikes, errors on DM threads, no YouTube support, and an auth-scope requirement surfaced via has_like_scope on list_inbox_connections. The retry warning after a missing-scope error is exactly the kind of operational context the annotations cannot carry.

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?

Four dense sentences, front-loaded with what the tool does, then platform/thread constraints, then the auth prerequisite. No filler and no repetition of the schema's optional-parameter text.

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?

For a two-required-parameter mutation with no output schema, the definition covers what is mutated, which resource kinds are valid, which platforms are excluded, the auth prerequisite, and the retry policy. An agent can call it correctly and handle the main failure mode without extra lookups.

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%, so every parameter including the idempotency key and workspace auto-resolution is already documented in structured form. The description restates liked=true/false semantics rather than adding syntax or format detail beyond the schema, so the baseline 3 applies; the thread_kind constraint is useful but is not a parameter.

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 first sentence names a specific verb and resource: setting the 'liked by us' state on a top-level comment thread, with the platforms scoped (Instagram or Facebook). It also carves out DMs and YouTube, which effectively separates it from the sibling like_message without ambiguity.

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?

Explicit when/when-not guidance: only thread_kind post_comments or video_comments can be liked, DMs return an error, and YouTube is unsupported because Data API v3 lacks a like endpoint. It also states a prerequisite (like scope) and a behavioral rule (don't retry until the user opens the error link).

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