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discoverNicheTrends

Identify YouTube trends in specific niches with momentum signals, saturation analysis, and content gap opportunities to guide video content strategy.

Instructions

Discover what's trending in a niche right now. Returns top-performing and recent videos, momentum signals (accelerating/steady/decelerating), saturation analysis, content gap opportunities, keyword patterns, and format breakdown. Grounded in YouTube search data with honest limitations disclosed. [~5-15s]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nicheYesThe niche or topic to explore, e.g. 'AI coding tools', 'home espresso', 'Kubernetes tutorials'
regionCodeNoISO 3166-1 alpha-2 country code, e.g. US, AU, DE
maxResultsNo
lookbackDaysNo
dryRunNo
Behavior4/5

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

With no annotations provided, the description carries full disclosure burden. It succeeds by revealing the data source ('YouTube search data'), execution latency ('[~5-15s]'), and claiming 'honest limitations disclosed', though it omits specific mutation/safety characteristics or rate limit details.

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 efficiently front-loaded with purpose, followed by specific return values, data provenance, and timing metadata. Every clause earns its place with zero redundancy—optimal information density for agent consumption.

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 the complexity of outputs (saturation analysis, momentum signals) and lack of output schema, the description adequately details return structure and scope. It appropriately omits low-level parameter schemas but could clarify dryRun semantics or failure modes for complete coverage.

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 coverage is only 40% (3 of 5 parameters lack descriptions). While the description implies 'recent videos' maps to lookbackDays and 'top-performing' hints at maxResults, it fails to explicitly document dryRun behavior or the interaction between lookbackDays and momentum calculations, providing only partial compensation.

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 opens with the specific action 'Discover' applied to 'what's trending in a niche right now', and immediately distinguishes itself from sibling tools like 'findVideos' or 'exploreNicheCompetitors' by detailing specific analytical outputs: momentum signals, saturation analysis, content gaps, and format breakdowns.

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 temporal context ('right now', 'momentum signals', 'recent videos') suggesting use for current trend analysis, but provides no explicit when-to-use guidance, alternatives for historical analysis, or cautions against using for saturated markets.

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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