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reeling_adapt_content_ai

Use Reeling's AI content adapter to transform a single hook, script, or topic into platform-tailored copy for TikTok, Instagram Reels, YouTube Shorts, Threads, and Bluesky.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toneNoOptional tone: 'engaging', 'humorous', 'educational', 'viral', 'professional'.
topicYesCore topic, transcript, or draft text to adapt.
api_keyNoOptional Reeling API key.
platformsNoTarget platforms to generate copy for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses almost nothing beyond the transformation itself: no statement about output format, determinism, latency/cost, or the fact that api_key is optional-only-when-needed. For a generative tool with zero annotation coverage this is a significant gap.

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?

A single well-formed sentence with the action verb front-loaded and the platform list at the end. No filler, though it is thin for the amount of behavior an annotation-free tool must explain.

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 four parameters, no output schema, and no annotations, the description is the only source of behavioral context and it covers essentially just purpose. It is minimally adequate for calling the tool but leaves output shape, platform constraints, and auth behavior unstated.

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%, so the schema already documents topic, tone, platforms, and api_key; the description adds only a loose mapping of 'hook, script, or topic' to the topic parameter and implies which platforms are supported. Baseline 3 is appropriate when the schema carries the detail.

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?

States a specific verb (transform) and inputs (a single hook, script, or topic) and names the concrete target platforms, so the resource and scope are unambiguous. It does not differentiate itself from siblings such as reeling_evaluate_content_jev or reeling_generate_video, so it stops short of a 5.

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 imperative 'Use ... to transform' implies the use case, but there is no explicit when-to-use vs. alternatives, no exclusions, and no mention of when the sibling evaluate/generate tools would be preferable. Usage is implied rather than guided.

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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