Taseli

Meta ad set health

get_ad_set_health

Read-onlyIdempotent

Every running Meta (Facebook and Instagram) ad set: Meta's learning status (learning, learned, learning limited), results in the last 7 days against the ~50 a week Meta needs to finish learning, daily budget, and this week vs last week of reach, frequency (how often each person saw the ads) and CTR, with a flag when the audience is tiring. Useful for 'is Meta still learning?', 'why is the cost jumping?', 'are people tired of my ads?'.

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_ad_set_health"
  }
}

Input Schema

Name	Required	Description	Default
`account`	No	An ad account's name, to look at one account; omit for all of them.
`language`	No	Answer language. The business's language by default.

Output Schema

Name	Required	Description
`note`	No	A plain note instead of data (nothing connected yet, not available here).
`error`	No	Why nothing was done, as a short code.
`truncated`	No
`truncatedNote`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 3, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds real behavioral context beyond them: scope limited to *running* ad sets, a 7-day measurement window, an explicit ~50-conversions-per-week benchmark, and a fatigue flag that implies a computed judgment rather than raw data.

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 the resource and then the metric list, followed by example questions that reinforce scope. It is a single dense sentence plus a short second one, with no filler, though the metric enumeration is long enough that a brief grouping would read faster.

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?

An output schema exists, so return values need no explanation, and the annotations cover the safety profile. The description supplies the remaining essentials — which ad sets, which metrics, over what window, and what threshold defines 'learning' — leaving no material gap for correct invocation.

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% and both parameters (account, language) are documented in-schema, so the description's silence on them is acceptable. It adds no meaning beyond the schema — no note on what happens when account is omitted or how language affects the metric labels.

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 concrete resource (every running Meta ad set) and enumerates the exact payload: learning status, results over 7 days vs. the ~50/week threshold, daily budget, week-over-week reach/frequency/CTR, and a fatigue flag. An agent can distinguish this from reporting siblings like get_results or get_account_review without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit triggering questions ('is Meta still learning?', 'why is the cost jumping?', 'are people tired of my ads?'), which is strong when-to-use guidance. It stops short of naming an alternative or an exclusion (e.g., use get_results for account-level totals instead), so routing between siblings is still partly inferred.

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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