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Apogee: Bulk Ad Launcher for Meta, TikTok & Snapchat

by ad.apogee
OverviewDiscussionsAdmin

Meta ad comments

fetch_ad_comments
Read-onlyIdempotent

What people say under Meta ads: objections, praise and questions, in their own words. Read ad comments from the shared DB (populated by the Comment Analysis feature). Returns messages, authors, like counts, whether the page replied. Use for extracting customer language, objections, praise, and pain points. IMPORTANT: if the user asks about "all ads" or "account-wide", call WITHOUT ad_ids/post_ids to get every comment for the ad account in one query. Use ad_ids/post_ids only to narrow down to specific ads. If no data is found, tell the user to run Comment Analysis sync first.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ad_account_id": "<ad_account_id>"
    },
    "name": "fetch_ad_comments"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax comments to return (default 200, max 1000).
ad_idsNoOptional: narrow to specific Meta ad IDs.
post_idsNoOptional: narrow to specific Facebook/Instagram post IDs.
since_daysNoOnly return comments created in the last N days (default 30).
ad_account_idYesMeta ad account id (act_…), from list_ad_accounts

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds real value beyond that: the data provenance (shared DB populated by the Comment Analysis feature), the returned fields (messages, authors, like counts, page-reply status), and the empty-result behavior. It does not mention pagination or freshness/latency of the synced data, which keeps it from 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-loaded with the resource and the key scoping rule, and the IMPORTANT marker correctly flags the most error-prone decision. The opening sentence is slightly promotional ('in their own words') and could be trimmed, but overall it is dense and purposeful.

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

Completeness4/5

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

With no output schema, the description compensates by enumerating the returned fields and the empty-state handling, and it explains the data source dependency. For a read-only filtered-list tool this is nearly complete; only pagination/volume behavior and data staleness are unaddressed.

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%, so the baseline is 3, but the description adds semantics the schema cannot express: the interaction between ad_ids/post_ids and account-wide scope, and the default behavior when they are omitted. It does not elaborate on limit or since_days beyond the schema, which is fine since those are already documented.

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 ('Read ad comments from the shared DB') plus the content domain (objections, praise, questions). It is clearly distinguishable from siblings like fetch_customer_reviews and search_reddit, which cover different sources.

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 explicit when-to-use guidance ('extracting customer language, objections, praise, and pain points') and a concrete routing rule: omit ad_ids/post_ids for account-wide requests, use them only to narrow. It also names the remedy for an empty result (run Comment Analysis sync), which is effectively the alternative path.

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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