CoreWise

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.

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.

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.

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.

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.

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.

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses async status handling (polling), the result structure upon completion, and API key requirement. It doesn't detail error cases or other statuses (e.g., failed), but for a read tool this is reasonably 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 two sentences, front-loaded with the main purpose, and includes useful operational details. Every sentence serves a purpose without redundancy.

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 single-parameter retrieval tool with no output schema and no annotations, the description thoroughly covers usage context, response format, and polling behavior. It even specifies the exact structured synthesis fields and per-model markdown summaries, making it self-sufficient.

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?

The schema already provides 100% coverage for the single parameter, describing extraction_id as 'The extraction id returned by extract_url.' The description doesn't add parameter-specific details beyond the id, so the baseline of 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 tool 'gets the status and results of a CoreWise extraction by id', which is a specific verb+resource+scope. This distinguishes it from siblings like extract_url (creation) and get_transcript (transcript retrieval).

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 advises polling every 20-30 seconds while processing and explains what to expect when completed. It also clarifies access scope (own extractions with API key, public community extractions). It doesn't explicitly mention alternatives, but the sibling tool purposes are sufficiently different that no confusion arises.

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?

With no annotations, the description carries full burden and delivers: timing (available before completion), pagination behavior (truncated flag), access scope (own extractions with API key, public community extractions), and length caveat. This exceeds the typical transparency bar and gives agents a clear operational model.

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 sentences, each earning its place: purpose, timing+access, and paging. Front-loaded with the core action, no redundancy. Perfectly sized for its content.

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 3 params, no output schema, and no annotations, this description covers all essential aspects: what it returns (raw text), when it's usable, how to handle long transcripts, and authentication scope. It anticipates likely agent questions and leaves little ambiguity.

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%, but the description adds meaningful context by explaining the paging workflow: pass offset and max_chars when truncated is true. This ties parameters to a behavioral pattern not evident from the schema alone, elevating it above the baseline.

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 opens with a specific verb and resource: 'Get the raw source transcript (or article/PDF text) of a CoreWise extraction by id.' This clearly distinguishes it from siblings like extract_url (creation), get_extraction (metadata), and search_public_extractions (search). The scope is explicit and unambiguous.

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?

It provides strong when-to-use guidance: 'Available as soon as the extraction has been initialized — no need to wait for completed' and explains paging with offset and max_chars. It does not explicitly mention alternatives, but the context implies using this for transcript content versus other tools for metadata or search. Lacks an explicit 'use X instead' statement, so not a 5.

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?

With no annotations, the description carries the full burden. It discloses the data scope (public community library), return contents (titles, snippets, share URLs), and that no API key is required. These are meaningful behavioral traits not implied by the schema.

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 the core purpose, then adds the use case and a final note on authentication. Every sentence earns its place with no redundancy.

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 search tool with two parameters and no output schema, the description covers the essential context: what is searched, what is returned, the intended use case, and authentication. It is sufficiently complete for the tool's simplicity.

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?

Both parameters are fully described in the schema (100% coverage), including default/max for limit and matching for query. The tool description adds no extra parameter semantics, so the baseline of 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 a specific verb ('Search') and a specific resource ('CoreWise's public community library of extractions'), and distinguishes the tool from siblings by focusing on searching existing extractions rather than creating or retrieving single 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 provides a clear use case: 'Useful to check whether a video has already been extracted before starting a new extraction.' This gives timely context and implies the alternative of starting a new extraction (i.e., using a sibling tool), though it doesn't explicitly name the alternative tool.

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