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nidhipati — proof of spend for AI agents

Audit an agent's spending records

audit_spend
Read-only

Find duplicates, price escalation, failed-but-billed calls, runaway loops, missing refunds, model overpay, unknown asset/network and budget breaches in a list of settled agent calls. Returns three separate amounts (money without a basis, estimate above the agent's own median, budget overrun) instead of one sum, because adding them together would overstate what can be recovered. Do NOT use as a statement of money actually returned.

Input Schema

NameRequiredDescriptionDefault
policyNoOptional budget policy: {"limit_usd": "100"}.
recordsYesRows with ts, agent_id, tool, quote, settled, status; optional model, actual, refund, asset, network, tx_hash, payee.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description goes beyond them by disclosing a non-obvious return behavior: three separate amounts rather than one sum, plus the rationale that summing them would overstate recoverable money. What remains undisclosed is whether findings are per-record or aggregated, and whether 'records' is validated or silently skipped when malformed.

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?

Front-loaded with the action verb and the anomaly list, then a second sentence that explains the unusual three-amount return shape and its rationale. Dense but every clause earns its place; the anomaly enumeration is long but directly useful for matching against a caller's intent.

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?

With no output schema, the description appropriately explains the return structure (three separate amounts) and warns against misinterpreting it. Combined with a fully documented input schema and read-only annotations, the definition is sufficient to select and invoke the tool; only the granularity of per-finding results is left to guesswork.

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% and the schema documents both 'records' (row fields incl. ts, agent_id, tool, quote, settled, status) and 'policy' (limit_usd). The description adds no syntax or format guidance for either parameter; 'budget breaches' only obliquely signals that the policy parameter drives that check. Baseline 3 is appropriate when the schema carries the parameter burden.

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 uses a specific verb ('Find') against a precisely scoped resource (settled agent calls) and enumerates the anomaly classes it detects: duplicates, price escalation, failed-but-billed calls, runaway loops, missing refunds, model overpay, unknown asset/network, budget breaches. An agent can tell this is an anomaly-detection pass over a supplied list rather than a reconciliation, verification, or report-resolution step.

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?

It gives one explicit when-not ('Do NOT use as a statement of money actually returned'), but that is an interpretive warning about the output, not a routing rule between tools. No sibling (reconcile_books, verify_receipt, resolve_report, reserve_report) is named, and no precondition such as 'call after settlement' is stated.

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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