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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, but the description adds genuinely new behavior: reads do not count toward the monthly change limit, and an identical read within 30 seconds may return cached data (see data_age_seconds). That caching disclosure is exactly the kind of non-obvious trait that saves an agent from misreading stale results.

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 twelve-operation bullet list is largely justified because the tool_name routing requires knowing available operation names, but the preamble wastes its most prominent sentences on Meta references and meta-commentary about list_tools instead of front-loading what the tool is. The critical routing example is buried mid-paragraph rather than leading.

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 no output schema, the per-operation bullets usefully describe what each read returns (spend, CTR, ROAS, review reasons, change attribution), which is the main burden here. The residual gap is the platform mix-up: an agent reading only the first line could conclude this touches Meta rather than TikTok ad accounts.

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 the baseline is 3, and the description exceeds it by supplying a concrete invocation example ({"action":"execute","tool_name":"list_campaigns","arguments":{}}) and noting that "connection" is needed when several ad accounts are connected. The Meta/TikTok confusion in the preamble slightly muddies which account identifiers apply.

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 opening sentence, "Reads Meta ad accounts," names the wrong platform entirely and contradicts the tool name/title (TikTok), which is a real risk of misselection against meta_ads_read. The bulleted enumeration of twelve tiktok_* operations does eventually make the purpose unambiguous, but the agent has to read past a misleading lead to get there.

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 clearly explains the two-mode pattern — list_tools to discover operation names and fields, execute to run one read — and states that list_tools is free and makes no API call. What it does not do is tell the agent how to choose between this router and platform siblings like meta_ads_read, google_ads_read, revenue_report or performance_dashboard.

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