Update dunning (payment recovery) configuration for an organization. All fields except organizationSlug are optional — only provided fields are updated, rest stays unchanged.
| Name | Required | Description | Default |
|---|---|---|---|
| steps | No | ||
| enabled | No | ||
| blockOnStep5 | No | ||
| gracePeriodDays | No | ||
| organizationSlug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It does disclose a key behavior: the partial-update semantics ('rest stays unchanged'). However, it does not mention auth requirements, reversibility, side effects on existing configuration, or error behavior. This is a mutation tool, so more transparency would be beneficial, but the partial-update disclosure adds meaningful value.
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), front-loaded with the primary purpose, and every sentence contributes information. It avoids fluff and gets straight to the point while including the important partial-update detail.
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?
This is a configuration tool with 5 parameters, one being a nested array of objects, and no output schema. The description does not explain the steps array structure, what blockOnStep5 or gracePeriodDays control, or what happens after the update. It is minimally viable but insufficient for an agent to confidently invoke the tool with correct nested data.
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 description coverage is 0%, so the description must compensate. It adds optionality information ('All fields except organizationSlug are optional') but does not explain the meaning of the 'steps' array, its nested structure (step, channel, daysAfterDue), or the purpose of 'blockOnStep5' and 'gracePeriodDays'. The schema names provide some hints, but the description fails to clarify the expected format for a complex nested parameter.
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's function: 'Update dunning (payment recovery) configuration for an organization.' It uses a specific verb ('Update') and resource ('dunning configuration'), and clarifies the domain term 'dunning' as 'payment recovery'. It also distinguishes itself from the sibling tool 'dunning_get_config' by contrasting update vs. get operations.
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 explicit usage guidance: 'All fields except organizationSlug are optional — only provided fields are updated, rest stays unchanged.' This tells the agent when to use it (partial updates) and clarifies that not all fields need to be supplied. However, it does not explicitly mention alternatives or when not to use it, such as referencing dunning_get_config for reading current configuration.
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.
Multiple parallel booking creation flows (booking_create, scheduling_book, public_booking_create) and session state transition tools (booking_update_status, lifecycle_transition) create ambiguity. While descriptions are detailed, an agent could easily select the wrong tool for a given task, especially with 111 tools to choose from.
Most tools follow a consistent domain_action pattern (e.g., client_create, service_update, comms_list_campaigns). Minor deviations include Spanish/English mixing (cierre_*, report_deuda_real) and a few noun-only names like org_summary, but the overall structure is predictable.
With 111 tools, the server is massively over-scoped for an MCP surface. Even for a broad service business domain, this exceeds reasonable limits and will overwhelm agents, making tool selection slower and more error-prone.
The tool surface is extremely thorough, covering org setup, services, providers, booking (internal/public/spec), finance, payroll, closing, disputes, clinical notes, treatment plans, and reporting. Gaps are rare and often intentional (e.g., no deliver via MCP, read-only treatment plans), so agents can complete most workflows end-to-end.