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get_competitor_ads

Retrieve competitor ad creatives and copy from Meta and Google Ads to analyze marketing strategies and identify opportunities.

Instructions

Get scraped ads for a specific competitor including creative previews and copy. competitor_id must come from list_competitors — match by brand name, then use the internal ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
competitor_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It implies a read-only operation ('Get') and specifies data source ('scraped ads'), but doesn't disclose behavioral traits like rate limits, authentication needs, or what happens if the competitor_id is invalid. It adds some context about the ID source, but lacks details on response format or potential errors.

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 zero waste. The first sentence states the purpose and scope, and the second provides essential usage guidance. It's front-loaded with the core action and efficiently conveys necessary information without redundancy.

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?

Given 1 parameter with 0% schema coverage and an output schema (which handles return values), the description is mostly complete. It covers purpose, parameter semantics, and usage context. However, as a read tool with no annotations, it could benefit from mentioning behavioral aspects like data freshness or limitations, but the output schema reduces this need.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It adds crucial meaning beyond the schema: 'competitor_id must come from list_competitors — match by brand name, then use the internal ID.' This explains how to obtain and validate the parameter, which is not in the schema. For a single parameter with no schema documentation, this is excellent compensation.

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 clearly states the verb 'Get' and resource 'scraped ads for a specific competitor', specifying it includes 'creative previews and copy'. It distinguishes from siblings like 'analyze_account_ads' or 'scrape_competitor_ads' by focusing on retrieval rather than analysis or scraping. However, it doesn't explicitly contrast with all siblings, such as 'get_account_analysis' or 'get_scrape_status'.

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?

It provides clear context: 'competitor_id must come from list_competitors — match by brand name, then use the internal ID.' This tells when to use (after identifying a competitor via list_competitors) and how to obtain the parameter. It doesn't explicitly state when not to use or name alternatives like 'scrape_competitor_ads' for new data, but the guidance is sufficient for correct invocation.

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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