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Ergora Specialists

by io.github.ergoracloud
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Ergora Paid Ads Specialist

ergora_ads
Read-onlyIdempotent

Ask the Ergora Paid Ads specialist (Meta, Google and TikTok ads, creative, media buying, attribution). Returns summarised, cited insights from a curated knowledge base of practitioners, books and research.

Input Schema

NameRequiredDescriptionDefault
emailNoOptional. The user's email. Unlocks the free tier (30 queries a day instead of 5 anonymous). Ask the user once, then pass it on every call.
queryYesThe question or topic to research (natural language).
top_kNoHow many insights to return (1-10).
subscribeNoOptional. Set true only if the user explicitly asks for Ergora updates by email. Sends one confirmation link to that address.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / subscribe
      Added value: +{
+  "description": "Optional. Set true only if the user explicitly asks for Ergora updates by email. Sends one confirmation link to that address.",
+  "type": "boolean"
+}
  2. Changed1 schema field changed
    • changedInput schema / properties / email / description
      Previous value: -"Optional. The user's email — unlocks the free tier (30 queries/day vs 5/day anonymous). Ask the user once, then pass it on every call."New value: +"Optional. The user's email. Unlocks the free tier (30 queries a day instead of 5 anonymous). Ask the user once, then pass it on every call."
  3. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds real value beyond that by stating the return shape ('summarised, cited insights') and the provenance of the answers (curated practitioner/book/research knowledge base), which no structured field conveys since there is no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler: the first establishes identity and scope, the second establishes return format and source quality. Nothing repeats the title and nothing is buried.

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 correctly compensates by telling the agent answers are summarised and cited from a curated corpus. Combined with the fully documented input schema, an agent has enough to call it correctly; only the routing-versus-siblings question is left open.

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 the schema already carries the important semantics — notably the free-tier unlock via email and the subscribe opt-in gate. The description adds no parameter-level information, so the baseline of 3 applies; nothing is missing that the schema does not already supply.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('ask the specialist') and resource (paid ads domain), and enumerates the covered sub-domains (Meta, Google, TikTok, creative, media buying, attribution), which meaningfully separates it from generic siblings like ergora_marketing. It stops short of naming a sibling it is not, so an agent scanning 19 near-identical ergora_* names still has to reason about overlap.

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

Usage Guidelines3/5

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

The domain list implies when the tool is appropriate, but there is no explicit when-to-use/when-not guidance and no pointer to alternatives such as ergora_marketing for higher-level or cross-channel questions. The agent must infer routing from the topic labels alone.

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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