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Action history

get_action_history
Read-only

Return the tenant-wide audit log of changes agentcentral made (bids, budgets, keywords, negatives, targets, states, listings, and other writes), newest first. This is the reliable record of what the agent changed and when, including for reconstructing what changed around a performance shift; Amazon's own change history (get_ads_change_history) does not include API/agentcentral changes. Requires the active API key to include agent_actions:read; if allowed, returns actions submitted by all keys in this tenant, not just the caller key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinNoOptional ASIN filter for historical audit rows that populated asin.
limitNoMaximum rows to return, newest first (1-500, default 100).
domainNoOptional write domain filter. Currently audited write actions are in ads, catalog, and fulfillment.
offsetNoPagination offset (0-100000, default 0). Use the returned pagination.next_offset to continue.
targetNoOptional substring match against the audit target field, such as campaign:123, keyword:456, or listing:SKU:price.
end_dateNoOptional YYYY-MM-DD upper bound for action timestamp. Defaults to today.
tool_usedNoOptional exact MCP write tool name filter.
profile_idNoOptional Amazon Ads/Seller profile ID filter.
start_dateNoOptional YYYY-MM-DD lower bound for action timestamp. Defaults to 30 days ago.
action_typeNoOptional exact audit action type filter.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
evidenceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/destructive annotations, it discloses the required permission scope (agent_actions:read), the surprising tenant-wide visibility (returns actions from all keys in the tenant, not just the caller), the newest-first ordering, and the audited write classes. This is exactly the kind of cross-cutting behavior an agent cannot infer from 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?

Three sentences, front-loaded with purpose, then the differentiating value, then the auth/scope caveat. It is denser than strictly necessary — the annotation of audited write types could be trimmed — but every clause carries distinct information and no filler.

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

Completeness5/5

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

Output schema is present so return values need no explanation; the description still covers the safety profile, required permission, cross-key scope, ordering, and pagination hint. For a 10-parameter, zero-required audit tool, nothing an agent needs to call it correctly is missing.

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 each of the 10 parameters is already documented (ranges, defaults, filter semantics, pagination via next_offset). The description adds no syntax or format detail beyond that, so the baseline 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?

States a specific verb and resource ('Return the tenant-wide audit log of changes agentcentral made') plus the exact write categories audited (bids, budgets, keywords, negatives, targets, states, listings). It also explicitly distinguishes itself from the sibling get_ads_change_history, so an agent can tell the two apart without opening a schema.

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?

Names the concrete use case ('reconstructing what changed around a performance shift') and routes away from the alternative by explaining that Amazon's own change history (get_ads_change_history) omits API/agentcentral changes. The condition selecting this tool over the sibling is explicit.

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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