list_bills_owedList the contractor/vendor bills the business still owes, with balance due and how overdue each is. Answers "what bills do I still need to pay?"
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| bills | Yes | ||
| count | Yes | ||
| total | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint true and destructiveHint false, so the agent knows it is a safe read. The description adds detail about the returned fields (balance due, overdue status), but does not disclose pagination or limits. With good annotations, this is adequate.
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?
Two succinct sentences deliver the purpose and a usage example. No filler or redundancy.
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 likely informative output schema, the description fully covers the tool's purpose and result. It answers a common user question.
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 no parameters, and schema coverage is 100%, so the description does not need to add parameter info. Per guidelines, 0 parameters gives a baseline of 4.
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 clearly states the tool lists contractor/vendor bills still owed, including balance due and overdue status, answering a specific question. It is distinct from sibling tools like list_outstanding_invoices which deal with invoices sent to clients.
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 implies usage for viewing unpaid bills but does not explicitly state when to use this tool versus alternatives like list_outstanding_invoices. No exclusions or context are provided.
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.
Each tool targets a specific financial, client, project, or tax aspect with clear, distinct descriptions. Overlaps like get_cost_summary vs get_expense_summary are resolved by explicit scope differences (costs include mileage and bills; expenses are line-item). No two tools serve the same purpose.
All 25 tools follow a strict `verb_noun` pattern: `get_` for detailed summaries and `list_` for enumerations. No mixed conventions (camelCase, abbreviations) are present, making the pattern predictable for an agent.
At 25 tools, the set is on the larger side but fully justified by the breadth of the domain (financial summaries, clients, projects, taxes, contacts, time, mileage). Each tool covers a distinct slice; minor redundancies (e.g., cost vs expense summary) are acceptable due to nuanced differences.
The surface covers essential business operations: revenue, costs, expenses, cash, invoices, bills, projects, clients, contacts, taxes, time, mileage, and goals. Notably missing are any mutation tools (create/update), but the server appears intentionally read-only (analytics/reporting). For that purpose, the coverage is strong.