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Update a customer

update_customer
Destructive

MUTATES Autumn billing data — partially updates a customer. Only provided fields change. Autumn API: POST /v1/customers.update.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoCustomer's name.
emailNoCustomer's email address.
currencyNoCurrency to bill this customer in (e.g. usd, eur).
metadataNoArbitrary key/value metadata for the customer.
stripe_idNoStripe customer id.
customer_idYesID of the customer to update.
fingerprintNoDuplicate-detection fingerprint.
new_customer_idNoNew id for the customer.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark destructiveHint=true, and the description reinforces this with 'MUTATES'. It adds meaningful behavioral context with 'Only provided fields change', making the partial-update semantics explicit and reassuring agents that unspecified fields are left untouched. This goes beyond what the annotation alone conveys.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. The mutation signal and partial-update behavior are front-loaded, and the endpoint reference provides useful context without bloating the text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with a destructive hint and no output schema, the description provides the essential behavioral context: mutation, partial update, and endpoint. The full parameter schema compensates for the absence of parameter-level prose. It lacks explicit alternative routing, but what is present is sufficient for an agent to invoke the tool correctly in most cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents every parameter. The description adds the general semantic that only provided fields change, which is useful but does not deepen understanding of individual parameters such as stripe_id, fingerprint, or new_customer_id beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('partially updates a customer') on a specific resource ('Autumn billing data'), making the tool's purpose unambiguous. It distinguishes itself from sibling read tools like get_customer and list_customers by emphasizing mutation, and from creation tools by saying 'partially updates' rather than creates.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not say when to use this tool versus alternatives such as get_customer, list_customers, or get_or_create_customer. The mutation cue is clear, but there is no explicit guidance on selecting update_customer over sibling tools, nor are any exclusions or prerequisites mentioned.

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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TDQS

A3.9/5.0
Disambiguation5/5

All tools have clearly distinct purposes: get/list for various resources, mutation tools like attach_plan, track_usage, and special tools like preview_attach and autumn_request for edge cases. No overlap in functionality.

Naming Consistency4/5

Most tools follow a verb_noun pattern (get_customer, list_plans, create_entity), but a few like autumn_request, preview_attach, and open_customer_portal break the pattern. Still, the naming is clear and predictable overall.

Tool Count4/5

18 tools is slightly above the typical 3-15 range, but each tool serves a distinct purpose in the billing domain, covering customers, plans, features, entities, invoices, usage, and portal access. The count is justified by the complexity of the domain.

Completeness4/5

The tool set covers CRUD for most resources (customers, features, plans, entities, invoices) plus billing operations like attach, check, preview, track usage, and customer portal. Missing delete operations and potential detach, but the read-only autumn_request may cover gaps. Minor gaps, not severe.