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CoreWise

by io.github.ryanportfolio

extract_url

Start an AI extraction of a YouTube video, podcast, article, or PDF URL on CoreWise. Returns an extraction_id immediately after initialization. Initialization normally takes a few seconds but can take up to 2 minutes for videos without captions or for PDFs. The extraction itself then runs for 1-7 minutes: poll with get_extraction every 20-30 seconds until status is 'completed'. Results include a cross-validated synthesis plus per-model summaries. Requires an API key (create one at corewise.video, Profile page, 'API & MCP Keys'). Each call consumes one extraction from the key owner's monthly quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe video, podcast, article, or PDF URL to extract insights from.
modelsNoWhich AI models to run (1-6). Default: ['openai', 'gemini']. More models cost more time.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / models / description
      Previous value: -"Which AI models to run (1-6). Default: ['claude', 'gemini']. More models cost more time."New value: +"Which AI models to run (1-6). Default: ['openai', 'gemini']. More models cost more time."
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses asynchronous behavior: immediate return of extraction_id, initialization delay up to 2 minutes, extraction duration of 1-7 minutes, result format (cross-validated synthesis plus per-model summaries), API key requirement, and quota consumption. This is highly transparent.

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 appropriately sized, front-loading the primary action and then providing necessary workflow details in a logical sequence. Each sentence earns its place, covering timing, polling instructions, results, auth, and quota without redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description covers the immediate return value (extraction_id) and directs users to get_extraction for polling. It explains the full lifecycle of the extraction, making it complete for an initiation tool.

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?

The input schema already provides 100% coverage for both parameters (url and models) with descriptions including defaults and trade-offs. The tool description does not add parameter-specific details beyond what the schema states, so the baseline 3 is appropriate.

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 'Start an AI extraction of a YouTube video, podcast, article, or PDF URL on CoreWise,' identifying the specific action and resource. It distinguishes itself from sibling tools by being the initialization step, while get_extraction polls and get_transcript retrieves transcripts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs to 'poll with get_extraction every 20-30 seconds until status is completed,' naming the sibling tool and defining the workflow. It also mentions API key requirements and quota consumption, giving clear when-to-use context and prerequisites.

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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TDQS

A4.6/5.0
Disambiguation5/5

Each tool serves a distinct function: extract_url initiates extraction, get_extraction retrieves structured results, get_transcript fetches raw source text, and search_public_extractions queries the public library. There is no overlap in purpose, and descriptions clearly differentiate them.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern (extract_url, get_extraction, get_transcript, search_public_extractions), all using lowercase snake_case. The verbs vary but the structure is uniform, making it predictable.

Tool Count5/5

Four tools precisely cover the server's scope: initiate, retrieve results, retrieve transcript, and search public content. This is an efficient size with no redundancy or missing essentials.

Completeness5/5

The tool set covers the full extraction lifecycle: create (extract_url), poll/read results (get_extraction), access raw data (get_transcript), and discover existing extractions (search_public_extractions). There are no obvious gaps for the stated purpose.

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