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get_timeline

Merged, date-ordered timeline of everything that happened to the business: interventions (changes the merchant applied, and when their verdict landed) plus store-context notes (campaign launches, migrations, budget freezes, data quirks the merchant recorded). Use this to line dated events up against a metric movement — 'revenue dipped on the 12th, what changed around then?' — instead of calling get_interventions and get_store_notes separately and stitching them yourself. Returns events sorted most-recent-first, each with a date, kind, store, and detail. Includes expired/closed items within the window so historical context isn't lost.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax events to return (default 50, max 200).
storeNoOptional. Filter to a specific store (short or full domain). Omit for all stores the caller can see.
_offsetNoPagination offset. If a response includes _pagination.hasMore=true, use _offset to fetch the next page.
endDateNoWindow end (YYYY-MM-DD). Defaults to today.
startDateNoWindow start (YYYY-MM-DD). Defaults to 90 days before endDate.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and delivers the highest-value traits: sort order (most-recent-first), the per-event shape (date, kind, store, detail), and that expired/closed items are retained within the window. It omits permission/auth scoping and rate-limit behavior, so it stops short of a 5.

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-loads the core definition and the alternative-routing rationale before the return-format note, with no filler. The parenthetical event-type list is dense but each item earns its place; slightly long overall.

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?

No output schema exists, and the description compensates by specifying the return ordering and per-event fields. Combined with the full-coverage input schema, an agent has everything needed to call and interpret the result.

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 the schema already documents limit, store, _offset, and the date window. The description only reinforces the windowing concept ('within the window'), adding no syntax or format detail beyond the schema; baseline 3 applies.

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+resource ('merged, date-ordered timeline of everything that happened to the business') and enumerates exactly what it merges: interventions and store-context notes. It explicitly names the sibling tools it replaces (get_interventions, get_store_notes), so an agent can distinguish it without opening any 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?

Gives an explicit use case ('line dated events up against a metric movement') with a worked example, and states the alternative it supersedes and why. When-to-use is unambiguous and directly contrasted with the two siblings it consolidates.

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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