List the Meta ad accounts connected to this Adbloop user, with the Page NAME + Instagram username + pixel each account uses. Use this to resolve a spoken account/page name to IDs.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true, so the description does not need to restate that. The description adds value by specifying the returned fields (Page NAME, Instagram username, pixel), which goes beyond the schema. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states the action and output details; the second gives the use case. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return values (Page NAME, Instagram username, pixel). For a simple list tool, this is adequate. It could mention pagination or filtering, but the tool has no parameters and is likely a straightforward list, so completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters and schema coverage is 100% (trivially). The description does not need to explain parameters. It correctly focuses on the output behavior, which is appropriate for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Meta ad accounts connected to the user, including specific details (Page NAME, Instagram username, pixel). It also provides a concrete use case (resolving spoken account names to IDs), distinguishing it from sibling tools that work with campaigns, adsets, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly suggests using the tool to resolve spoken account/page names to IDs, giving clear context. While it doesn't list exclusions or alternative tools, the read-only annotation and sibling list make it sufficiently clear that this is for account listing only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but creation tools (create_campaign, bulk_create_campaigns, create_structured, add_ad_to_adset) overlap in scope, potentially causing misselection. However, descriptions clarify differences.
All tool names follow a consistent verb_noun pattern in snake_case, such as 'bulk_create_campaigns', 'get_insights', 'pause_campaigns'. No mixing of conventions.
23 tools cover the Meta Ads domain well, but the count is slightly high. Most tools are justified, though some could be merged (e.g., creation variants).
Core CRUD is covered for campaigns and ads, but there is no tool to create an ad set independently (only via create_structured). Creative editing and standalone ad set creation are missing, leaving notable gaps.