Aident AI

Review Aident action history

audit

Read-only

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

Input 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

B3.2/5.0

Behavior3/5

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 adds that the tool surfaces USD cost alongside action calls, which is meaningful context beyond the annotations, but it says nothing about the mine/team wallet-visibility distinction or rate/volume limits.

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?

A single front-loaded sentence with no filler and the core capability stated first. It is arguably over-compressed for an 11-parameter tool, but nothing in it is wasted.

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?

With no output schema and 11 parameters, the description should carry more weight than one sentence. The schema covers most parameters, but the description omits the important scope semantics (team owner seeing shared-wallet usage), the required analytics parameters, and any clarification of the Aident/Loadout naming mismatch.

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 91%, so nearly every parameter is already documented in the schema, including the enum values for scope and action. The description adds no syntax, format, or default-value detail beyond that, so the baseline of 3 applies.

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 concrete verb pair ('Inspect or summarize') and a concrete resource ('recent Loadout action calls and their USD cost'), so an agent knows this is a read/aggregation tool over execution history. It does not, however, differentiate itself from the sibling 'billing' tool, which plausibly also deals with cost, nor does it reconcile 'Aident' in the title with 'Loadout' in the description.

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?

There is no explicit when-to-use or when-not-to-use guidance. The words 'recent' and 'inspect or summarize' hint at a usage context, but the description never tells the agent how to choose between this tool and 'billing' for cost questions, or when the summary mode is preferable to the recent mode.

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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