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get_business_context

Read-onlyIdempotent

Retrieve the durable business context a team has saved — guidelines, policies, and preferences — so analysis and changes follow them. Context is stored at three scopes, each read independently (a read returns one scope's entries, not a merge):

  • Team — applies everywhere (e.g. "report currency in EUR").

  • Data source — a specific platform (e.g. "for Meta, break out Advantage+ separately").

  • Account — a specific account (e.g. "this client reports last-click only").

Choose the scope with the ids: no ids → team level; ds_id → that data source's level; ds_id+account_id → that account's level. tags filters by category — a record matches if it carries any of the tags you pass (OR), and commas are just separators, so tags: ["a,b"] and ["a","b"] both match records tagged a or b. Omit tags to read all entries at the scope; tags with no ids searches across all scopes, so a tag lookup isn't confined to one level. Results are grouped as team/data_source/account (empty omitted); a single-source data-source list is keyed data_source:<ds_id>.

Prefer what the discovery tools already surface: data_source_discovery and accounts_discovery include team- and data-source-level context, and a narrowed accounts_discovery inlines an account's own context. Call this for a scope a discovery response did not cover — e.g. an account you are about to act on — to read tags whose context was too large to inline, or to re-read after a save.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_business_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
tagsNoCategories, comma-separated or JSON array, to filter by — a record matches any of them (OR). Omit to read every entry at the scope; with no ds_id/account_id, a tag lookup searches all scopes
ds_idNoData source code (e.g. AW, FA); scopes to data-source level
account_idNoAccount ID; requires ds_id; scopes to account level

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNo
notesNo
successYes
business_contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, non-destructive, but the description adds behavior annotations cannot express: the three scopes are read independently and results are NOT merged across scopes, tag matching is OR semantics with commas as mere separators, and omitting tags reads everything at the scope. It also discloses the result grouping keys (`team`/`data_source`/`account`, `data_source:<ds_id>`, empty omitted), which is genuinely useful for interpreting output.

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 purpose, then bullets for scopes, then a routing sentence — well organized and scannable. The tags paragraph restates schema text at some length, which is the main redundancy, but nothing is 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?

For a 3-param read tool with an output schema and full annotation coverage, the description supplies everything still missing: scope resolution rules, tag filter semantics, non-merging behavior, result keying, and sibling routing. An agent can call it correctly on the first try with no further inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already documents OR tag matching and the all-scope tag lookup, so the description is partly redundant there. However it adds meaning beyond the schema by spelling out the id-combination rule for scope selection (no ids → team, `ds_id` → data source, `ds_id`+`account_id` → account) and the consequence of pairing tags with no ids, which is the non-obvious interaction an agent would otherwise get wrong.

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 opens with a specific verb and resource — 'Retrieve the durable business context a team has saved — guidelines, policies, and preferences' — and immediately states the purpose ('so analysis and changes follow them'). It distinguishes itself from sibling discovery tools by name, so an agent can differentiate 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?

Explicitly says to prefer `data_source_discovery` and `accounts_discovery` since they already include context, and enumerates the exact conditions for calling this tool instead: a scope a discovery response did not cover, context too large to inline, or a re-read after a save. That is when-to-use, when-not-to-use, and alternatives all in one place.

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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