framefetch
Server Details
Any social-video URL → metadata, transcript, insights & frames (YouTube/TikTok/IG/Reddit/Pinterest)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.6/5 across 2 of 2 tools scored.
The two tools serve completely different purposes: one extracts data from a specific video URL, the other provides platform capabilities metadata. There is no overlap or confusion.
Both tools follow the consistent 'framefetch_' prefix with descriptive action words ('extract' and 'platform_capabilities'), maintaining a predictable pattern.
With only 2 tools, the server is minimal but well-scoped for its single-purpose domain. While slightly thin, it covers the primary actions needed.
The tool surface includes both capability checking and data extraction, providing a complete workflow for individual video URLs. Minor gaps like batch processing are absent but not critical.
Available Tools
2 toolsframefetch_extractAInspect
Extract structured data from ONE public social-video URL (YouTube incl. Shorts, TikTok, Instagram Reels, Pinterest, Reddit). Purpose: turn a video link into metadata (title, author, duration, date), insights (views/likes/comments), a transcript (captions, or Whisper when there are none — works on TikTok/Reddit too), and/or parametrically-sampled video frames. When to use: you have a video URL and need its text, stats, or frames for analysis, summarization, or grounding a model. When NOT to use: non-video pages, private/login-walled content, or bulk crawling (one URL per call). Returns: one JSON object containing only the requested fields plus a cost block (micro-USD). Frames come back as time-limited signed image URLs. Cost/latency: metadata is sub-cent and fast; transcript is billed per audio-minute and frames per frame (both also incur bandwidth) — request only the fields you need and downscale frames via width to control cost. Billing: a free tier covers light use; agents can also pay per call with x402 (USDC) with no account. Example: { "url": "https://www.youtube.com/watch?v=...", "fields": ["metadata","transcript"], "frames": { "mode": "fps", "fps": 1, "width": 480 } }
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public video URL from a supported platform. | |
| fields | No | Which data to return. Default ["metadata"]. Request the minimum you need. | |
| frames | No | Frame-sampling spec; required when "frames" is requested. | |
| verbosity | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It discloses key behaviors: single URL per call, return structure (JSON with cost block), frames as time-limited signed URLs, cost per field, and billing model. Could add error handling details but overall very transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured, front-loading the purpose and then detailing usage, return, and cost. Every sentence adds value, though some could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple platforms, variable cost, nested frames parameter), the description covers most essentials: supported platforms, use cases, return structure with cost, and billing. Minor omissions like error handling or rate limits are acceptable given the overall completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75% (3 of 4 parameters have descriptions). The description adds meaningful context beyond the schema, such as the cost implications of each field and an example of frames sampling. It clarifies the default for fields and explains the frames object parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts structured data from one public social-video URL, listing supported platforms (YouTube, TikTok, etc.) and distinguishing it from the sibling tool by focusing on extraction rather than platform capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly specifies when to use (video URL needed for text, stats, or frames) and when not to use (non-video pages, private content, bulk crawling). Provides cost and billing context to guide responsible usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
framefetch_platform_capabilitiesAInspect
Return a JSON matrix of which data types (metadata, insights, transcript, frames) each supported platform provides — YouTube, YouTube Shorts, TikTok, Instagram Reels, Pinterest, Reddit. Purpose: check what is available for a platform BEFORE calling framefetch_extract, so you only request supported fields. No input required.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description adequately describes a read-only, no-side-effect operation. It could mention if the lookup is lightweight or requires auth, but is sufficient for a simple capabilities check.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose and usage guidance. Every sentence earns its place with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description fully covers what it does, why to use it, and its relationship to the sibling tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; the baseline is 4. The description confirms 'No input required,' adding clarity beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a JSON matrix of data types per platform, with a specific verb and resource. It distinguishes itself from sibling tool framefetch_extract by stating its purpose as a prerequisite check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states to use BEFORE calling framefetch_extract to check available fields, providing clear when-to-use guidance and context.
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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{
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