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List credit transactions

list_credit_transactions
Read-only

Audit the organization's credit accounting log: grants (signup/monthly/pack/promo), debits (audit_base 50cr + audit_page 2cr per audited page + external_link 1cr per checked link + folded 0-cost services; older audits carry render rows instead of audit_page), refunds, and adjustments, newest first, paginated. Each debit/refund carries run_id so you can group a single audit's spend. Use this to explain why an audit cost what it cost or to reconcile a balance. For one audit's per-feature breakdown, use get_report (its cost field). Read-only.

Input Schema

NameRequiredDescriptionDefault
limitNoMax transactions to return (default 25, max 100).
cursorNoOpaque pagination cursor from a previous page's `next_cursor`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +{}
  2. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The description discloses ordering (newest first), pagination behavior, the grouping key run_id, and that it is read-only. Annotations already declare readOnly/destructive hints. It doesn't detail rate limits or result shape, but adds substantial useful context beyond annotations.

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

Conciseness4/5

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

The description is structured and mostly front-loaded with the purpose, then usage context. It is fairly dense and long but every clause is informative. Slightly over-packed with cost-detail examples, but no real waste.

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 no output schema and simple pagination parameters, the description is complete enough for an agent to invoke it correctly, covering what data it returns, ordering, grouping, and when not to use it. It could say more about the response item shape, but the key behavioral contract is present.

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 coverage is 100%, so the schema already documents limit and cursor semantics. The description mentions pagination and 'newest first' but does not add syntax or constraints beyond what the schema provides, so the baseline of 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 verb and resource: auditing the organization's credit accounting log, listing grants, debits, refunds, and adjustments. It distinguishes itself from the sibling get_report by explicitly naming the per-audit breakdown alternative.

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

Usage Guidelines5/5

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

It gives clear when-to-use cases (explain audit cost, reconcile a balance) and explicitly names the alternative (get_report's cost field) for per-feature breakdowns, so an agent knows when to choose this tool versus another.

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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