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eonik-ai

eonik-mcp

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get_ad_deconstruction

Retrieve the scene-by-scene deconstruction of any public ad: transcript, timing, role, shot type, camera, lighting, on-screen text, action, product visibility, dialogue. Analyze creative structure.

Instructions

eonik's scene-by-scene breakdown of a PUBLIC ad (a watched competitor, a category ad-library ad, a TikTok ad, or a swipe-file item): full transcript, genome, and every scene (timing, role, shot_type, camera, lighting, on-screen text, action, product visibility, dialogue). The labor eonik already did with ffmpeg + Whisper + Gemini, stored once per unique creative and reused across the fleet — use it to reason about creative STRUCTURE. Facts only. If none exists yet, call deconstruct_ad first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_idYesThe asset id of the public ad (watch asset / ad-library / tiktok / swipe).
Behavior4/5

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

With no annotations, the description carries the full burden. It states 'Facts only' (read-only) and explains that data is 'stored once per unique creative and reused' indicating no side effects. It does not specify error behavior when the asset_id is not found, but it does direct to deconstruct_ad for that case, leaving some ambiguity.

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

Conciseness4/5

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

The description is detailed but each sentence contributes useful information: content, methodology, storage, purpose, and fallback instruction. It is slightly verbose but not excessively so, and the structure flows logically from what to why to how.

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 (no output schema), the description adequately explains the return payload (transcript, genome, scene details) and the tool's purpose. It references the companion tool deconstruct_ad for creation, providing enough context for a user to understand when and why to call this getter.

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

Parameters4/5

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

The sole parameter asset_id is well-described in both the schema and the description, listing the valid ad sources. Since schema coverage is 100%, the baseline is 3; the description adds value by clarifying the 'public ad' context and the types of assets, so a 4 is warranted.

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 that the tool retrieves a precomputed scene-by-scene breakdown of a public ad, listing the exact content (transcript, genome, scenes with attributes). It distinguishes itself from sibling tools like deconstruct_ad by explicitly noting it fetches existing data and instructing to call deconstruct_ad if none exists.

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 a clear usage context: use to reason about creative STRUCTURE, and explicitly says to call deconstruct_ad first if no deconstruction exists. However, it does not contrast with other retrieval tools like search_competitor_ads or get_my_competitor_ads, so the guidance is not fully comprehensive.

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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