Aident AI

audit

Read-only

Inspect or summarize recent Loadout action calls and their USD cost.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum usage rows to inspect
`scope`	No	Use "team" as a team owner to see shared-wallet usage across active members	mine
`action`	No		recent
`dateTo`	No	Inclusive ISO timestamp upper bound
`status`	No	Filter by execution status
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`dateFrom`	No	Inclusive ISO timestamp lower bound
`agentName`	No	Filter by originating agent name
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`integrationId`	No	Filter to one integration ID or capability prefix
`requestSource`	No	Filter by caller source, such as mcp or cli

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedSep 14, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

addedInput schema / required

Added value: +[
+  "context",
+  "llm_model"
+]

Changed1 schema field changedAug 28, 2026

addedInput schema / properties / agentName

Added value: +{
+  "description": "Filter by originating agent name",
+  "type": "string"
+}

First observedAug 7, 2026

TDQS

B3.3/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds modest behavioral context by specifying that the tool inspects or summarizes cost data, but it does not disclose output format, default limits, or what the 'summary' mode produces.

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?

One direct, front-loaded sentence with no filler, repetition, or schema duplication. It communicates the core behavior efficiently and lets the schema carry parameter details.

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

Completeness3/5

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

The rich schema and read-only annotations cover parameters and safety, but the description is thin for an 11-parameter tool with no output schema. It does not clarify what a summary contains, how far back 'recent' reaches, or what return shape an agent should expect.

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 high (91%), so the parameters are largely self-documenting. The description adds little parameter-specific meaning beyond the schema, though 'Inspect or summarize' loosely aligns with the undocumented 'action' enum values 'recent' and 'summary'.

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

Purpose4/5

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

The description names a specific action ('Inspect or summarize') and a specific resource ('recent Loadout action calls and their USD cost'), making the tool's core purpose immediately clear. However, it does not explicitly distinguish itself from the 'billing' sibling tool, which could plausibly overlap on cost information.

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 gives no guidance on when to choose this tool over alternatives such as 'billing' or the capabilities tools, and it does not mention exclusions or prerequisites. The usage context is only implicit in the phrase 'recent Loadout action calls and their USD cost.'

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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