Returns the customer's invoices. @param customer_id: The customer's database id @return: a json object,in the "values" object containing one or more data rows in an object array
| Name | Required | Description | Default |
|---|---|---|---|
| customer_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description carries the full burden. It discloses the return structure (a JSON object with a 'values' array of data rows), which is useful. However, it does not explicitly state read-only behavior, error handling, or side effects.
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 compact and front-loaded, consisting of a purpose line, a parameter line, and a return line. There is minimal fluff, though the return statement has a minor grammatical awkwardness ('json object,in') and could be cleaner.
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 the tool's simplicity (one well-documented parameter, no annotations, no output schema), the description covers the essential aspects: what it does, the parameter semantics, and the return format. It lacks error behavior and comparison to siblings, but those are not critical for a basic getter.
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 input schema only gives the parameter type (integer), but the description adds '@param customer_id: The customer's database id', providing meaning beyond the schema. This compensates for the 0% schema description coverage.
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 states 'Returns the customer's invoices' with a clear verb and resource. It is specific enough to distinguish from sibling tools like customer_payment_history or customer_get_credit_balance, as it focuses on invoices.
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?
No guidance is provided on when to use this tool versus alternatives. It does not mention related sibling tools, prerequisites, or exclusions, leaving the agent without context for selection.
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.
Several tools have overlapping or identical purposes (e.g., netfluid__session and netfluid__session_2_token, netfluid__email and netfluid__send_email). With 142 tools spanning wallet, crypto, funding, and paywall features, distinguishing between similar account/crypto/balance tools requires careful reading of descriptions.
Most tools follow a snake_case pattern with a netfluid__ or paywall__ prefix, but there are inconsistencies like netfluid__session_2_token, netfluid__netfluid_voucher_check, and single-noun tools (netfluid__skill, netfluid__fees). The two namespaces use slightly different conventions, making the overall set feel less uniform.
At 142 tools, this is an extremely large surface for any MCP server. Even for a comprehensive financial platform, this exceeds practical usability and likely includes duplicates or overly granular operations.
The tool set covers a wide range of operations including account management, crypto transactions, funding methods, withdrawals, and paywall subscriptions. However, the presence of duplicate tools suggests redundancy rather than a clean, minimal complete surface, and some workflows may require chaining many tools.