check_balanceReturn the connected user's ProductClank credit balance and plan. Use before launching a campaign to confirm they have enough credits (a content campaign costs 1000; a reply boost 200; likes/reposts 300; a discovery campaign 10 to create + 12/post discovered).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=false, and the description adds useful behavioral context by specifying what is returned (balance and plan) and what the numbers mean in practice. It does not contradict the annotations, and it provides enough behavioral context for a zero-parameter read-only tool.
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 and front-loaded, stating the core purpose first and then giving the practical use case. The pricing details are directly relevant to the decision to call the tool and take up only one sentence.
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 parameters and a read-only annotation, the description is fully self-sufficient for an agent to know when and why to call it. It also supplies the important context of campaign credit costs, which helps the agent interpret the return value even without an output schema.
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?
There are zero parameters, and the schema description coverage is 100%, so parameter documentation is not a concern. The description helps by clarifying that the balance is for the connected user, which is the only relevant contextual semantic.
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 uses a specific verb ('Return') and identifies the exact resource (the connected user's ProductClank credit balance and plan), making the tool's function clear. It is distinct from the sibling credit_history by focusing on the current balance/plan snapshot, but it does not explicitly call out that difference.
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 tells the agent to use this tool before launching a campaign and gives concrete credit thresholds for different campaign types. It provides a clear trigger condition but does not mention when not to use it or point to alternatives such as credit_history.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools map cleanly to a distinct resource and action: campaigns, posts, products, research, content spaces, and submissions. A few pairs are close—`create_campaign` vs `create_content_campaign` and `check_balance` vs `get_earnings`—but the detailed descriptions make the intended selection clear.
The set largely follows a consistent `verb_noun` snake_case pattern (`list_campaigns`, `generate_posts`, `update_campaign`, `submit_participation`). Minor deviations keep it from a perfect score: `credit_history` lacks a verb, and `create_campaign` reads as generic next to the more specific `create_content_campaign`.
30 tools is high and makes the server feel heavy, but the domain genuinely spans products, credits, campaigns, research, post discovery, content spaces, boosts, and participation rewards. The breadth mostly earns the count, though it sits on the wrong side of the typical 3–15 range.
The core end-to-end workflow is covered: create and configure campaigns, discover and refine posts, run research, find opportunities, submit work, and measure results. Gaps exist but are minor for the central purpose—product listings can’t be updated or deleted, and delegates can be added but not removed.