CoreWise

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

With no annotations, the description fully discloses behavior: async nature, initialization timing (up to 2 minutes), extraction duration (1-7 minutes), polling recommendation, result contents (synthesis and per-model summaries), authentication requirement (API key), and quota consumption. No gaps or contradictions.

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 a single paragraph of about 100 words, front-loading the core function and then efficiently covering timing, polling, results, auth, and cost. Every sentence adds value with no redundancy or filler.

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 an async extraction tool with no output schema and two parameters, the description covers all necessary context: immediate return type, timing expectations, polling method, result contents, authentication, and quota. It is fully sufficient for an agent to correctly invoke and follow up.

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 100% with both parameters described. The description adds no additional semantic details beyond what the schema provides (url and models). The baseline is 3 due to high schema coverage, and description does not enhance parameter meaning further.

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?

Description clearly states it starts an AI extraction for specific URL types (YouTube, podcast, article, PDF) on CoreWise. The verb 'Start' and resource 'extraction' are specific, and it distinguishes from siblings by mentioning polling with get_extraction and not being a search tool.

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?

The description implicitly guides use by stating it returns an extraction_id for polling and that get_extraction is for checking status. It also mentions the quota cost and API key requirement, but does not explicitly state when not to use or compare to search_public_extractions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations provided, but description thoroughly covers behavioral traits: polling behavior, response structure with specified fields (JSON object with summary, takeaways, highlights, notable quotes, per-model markdown summaries), and auth conditions for own vs public extractions.

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?

Three efficient sentences: first states purpose, second gives usage guidance, third lists contents and access conditions. Front-loaded, no wasted words.

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 simple retrieval tool with one parameter and no output schema, the description covers all necessary aspects: purpose, when to poll (polling logic), what's in the response, and access scope (own vs public). Complete.

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 has 100% coverage for the single parameter extraction_id, but description adds useful context: confirms it comes from extract_url and implies it's a string identifier. Adds modest value beyond 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 verb (get), resource (extraction), and method (by id). It distinguishes from siblings: extract_url creates extractions, search_public_extractions searches, while this retrieves a specific extraction.

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?

Provides explicit polling guidance ('poll every 20-30 seconds') and indicates when status is 'completed'. Mentions authentication requirements for own extractions vs public. No explicit exclusion of alternatives, but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries full burden. It discloses return values (titles, snippets, share URLs) and that no API key is needed. However, it does not mention error handling, sorting, pagination details beyond the limit parameter, or behavior when no results are found.

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 three sentences front-loaded with purpose, no fluff, and every sentence adds value. It is appropriately sized for the tool's simplicity.

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 has 2 parameters, no output schema, and no annotations, the description covers purpose, return type, use case, and authentication. It lacks pagination or error details but is fairly complete for a simple search 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?

Schema coverage is 100% (both parameters described). The description adds no new parameter information beyond what is in the schema. For instance, the query parameter description in schema already says 'Search terms matched against titles and content'. So baseline 3 is appropriate.

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 verb 'Search' and the resource 'CoreWise's public community library of extractions', listing content types and stating it returns titles, snippets, and share URLs. It distinguishes itself from siblings (extract_url, get_extraction) by focusing on searching existing extractions.

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?

The description explicitly says it is 'useful to check whether a video has already been extracted before starting a new extraction', providing clear context. It also notes 'No API key required'. While it doesn't explicitly name alternatives, the sibling tool names and the context imply when to use this vs extract_url or get_extraction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.