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ahmedtawfeeq1

GenuDo Market Intelligence MCP

Search Meta Ads

search_meta_ads

Search public Meta Ad Library data by keywords and market to retrieve ad evidence for competitor analysis and market intelligence in Egypt, Saudi Arabia, and UAE.

Instructions

Search public Meta Ad Library data by keywords and market. This runs a paid Apify source Actor and stores normalized evidence for reuse.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoAlso fetch advertiser/social details. Slower and more expensive.
marketsNo
queriesYesEnglish and/or Arabic keyword queries.
active_onlyNo
results_per_queryNo
Behavior4/5

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

Annotations already indicate readOnlyHint false, but the description adds meaningful context: it discloses the paid nature of the underlying Actor and the side effect of storing normalized evidence. This goes beyond annotations, though it does not cover rate limits or authentication, which are less critical given the external API context.

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?

The description is only two sentences, front-loaded with the core purpose and followed by a key operational detail. Every word contributes, with no redundancy or filler.

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

Completeness3/5

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

With no output schema, the description does not clarify what the tool returns, which is a notable gap. It does provide context about paid execution and evidence storage, which helps, but it lacks guidance on output shape and relationship to sibling tools, making it only moderately complete.

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

Parameters2/5

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

Schema coverage is only 40%, and the description does little to compensate. It mentions 'by keywords and market,' which aligns with the queries and markets parameters, but it does not explain active_only, results_per_query, or the significance of deep beyond the schema's own description. The description adds marginal value over the schema.

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 clearly states the tool's function: 'Search public Meta Ad Library data by keywords and market.' This is a specific verb+resource+scope and distinguishes it from siblings like analyze_competitor_ads and get_market_evidence, which focus on analysis or retrieval of stored evidence.

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 description implies usage by mentioning 'runs a paid Apify source Actor and stores normalized evidence for reuse,' hinting that this fetches fresh data for later retrieval. However, it does not explicitly state when to use this tool versus alternatives like get_market_evidence or analyze_competitor_ads, leaving the usage context implicit.

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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