get_tokens_usageGet API token usage costs for different endpoints
Returns the number of tokens required for each API endpoint operation.
Note: eeatCompetitorsTokensCostPerCompetitor is a per-competitor cost.
The total cost of POST /api/v1/eeat-competitors equals this value × the number of
competitors analyzed (deduplicated URLs in the guide's top-10 SERP, capped at 10).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral information. It explains the return type (number of tokens per endpoint) and elaborates on the eeatCompetitorsTokensCostPerCompetitor field with a formula, but does not disclose authentication needs, rate limits, or read-only status. Adequate but not comprehensive.
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 concise: two sentences and a note, all essential. The note about per-competitor cost is front-loaded and adds critical detail without bloat.
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 zero parameters, no output schema, and no annotations, the description is nearly complete. It states what the tool returns and clarifies a non-obvious calculation. Minor omission: no mention of whether the output includes all endpoints or is filtered, but acceptable for a simple lookup tool.
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?
The tool has zero parameters, so no parameter-level description is needed. Per guidelines, baseline is 4 for no parameters.
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 and description clearly state 'Get API token usage costs for different endpoints', specifying the verb 'get' and resource 'token usage costs'. It distinguishes itself from siblings like get_credits and get_aissistant_tokens by focusing on token costs per endpoint.
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 provides no explicit guidance on when to use this tool versus alternatives. Context signals show siblings like get_credits for credit usage, but the description itself does not differentiate use cases or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources (guides, eeat, intent, internal_links, meta, outline, score, credits, tokens). However, some pairs like create_eeat and create_eeat_competitors are very similar and could cause confusion, though their descriptions clarify the difference.
Tools consistently use a verb_noun pattern (create_, get_, delete_). Minor inconsistencies include 'get_aissistant_tokens' (typo) and 'get_credit_ledger' (singular vs plural), but overall the pattern is clear.
28 tools is on the higher end but justifiable for a comprehensive SEO analysis platform covering guides, multiple AI features, EEAT, credits, and tokens. A few tools could be merged (e.g., get_credits and get_aissistant_tokens), but the count is still reasonable.
The tool surface covers CRUD for guides and most AI features, plus token/credit management. A notable gap is the lack of a get_score tool after create_score, and some features like updating EEAT analysis are absent. Overall, the core workflows are supported.