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Glama

List credit notes

codat_list_credit_notes
Read-only

List a company's credit notes (id, creditNoteNumber, customerRef, issueDate, currency, totalAmount, remainingCredit, status). Codat API: GET /companies/{companyId}/data/creditNotes. Returns the paged envelope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1).
queryNoCodat query filter string, e.g. "status=Paid" or "modifiedDate>2026-01-01". See docs.codat.io/using-the-api/querying.
orderByNoField to order results by, e.g. "-modifiedDate" (leading "-" for descending).
pageSizeNoRecords per page (1-2000, default 100).
companyIdYesThe Codat companyId (UUID).

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The description adds value beyond the readOnlyHint annotation by specifying that results are paginated (paged envelope) and listing the returned fields. It also gives the HTTP method and endpoint, providing context about the call behavior. No contradictions with annotations.

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 concise with three sentences: purpose with fields, API endpoint, and pagination behavior. Every sentence is informative and front-loaded, avoiding unnecessary detail.

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?

Given the tool's simplicity (list endpoint, 5 params fully described in schema, no output schema), the description covers the essential aspects: what it does, what data is returned, and that it's paginated. It does not address error handling or rate limits, but these are common and not critical.

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 baseline is 3. The description does not add significant meaning beyond the schema; it only lists returned fields which are not parameters. For parameter semantics, no extra value is provided.

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 clearly states the tool lists a company's credit notes and enumerates the fields returned (id, creditNoteNumber, etc.). It also specifies the API endpoint and that it returns a paged envelope, distinguishing it from siblings like list_invoices or list_customers by focusing specifically on credit notes.

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

Usage Guidelines3/5

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

The description implies usage when listing credit notes for a company, but does not explicitly state when to use this tool versus alternatives (e.g., list_invoices for invoices). No exclusions or context about when not to use it are provided.

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

A4/5.0
Disambiguation5/5

Each tool targets a distinct resource or action (e.g., companies, connections, invoices, financial statements). Even similar-looking tools like the three financial statements are clearly differentiated by their names and descriptions. No overlapping purposes.

Naming Consistency5/5

All tools follow the consistent pattern 'codat_verb_noun' (e.g., codat_create_company, codat_list_invoices, codat_get_balance_sheet). No mixing of styles or irregular naming.

Tool Count5/5

28 tools cover the main read and refresh operations across Codat's domain (companies, connections, accounting data, integrations). The count feels well-scoped for a data aggregation platform, not excessive.

Completeness3/5

The tool set focuses heavily on reading and listing data, with only create for companies/connections and refresh triggers. Missing update/delete for many entities (e.g., invoices, bills). An escape hatch exists but is GET-only. Notable gaps for write workflows.