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houtini-ai

@houtini/contentmarketingideas

Official
by houtini-ai

populate_corpus

Scrape and index up to 20 URLs to add their content to the RAG corpus, providing source material for content marketing ideas.

Instructions

Add URLs to the RAG corpus (scrapes and indexes them, max 20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesURLs to scrape and index
Behavior3/5

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

With no annotations provided, the description must carry the full weight of behavioral disclosure. It does disclose that the tool scrapes and indexes URLs and includes a max limit of 20, which is helpful. However, it omits other behavioral details like whether duplicate URLs are checked, if the operation is synchronous, or what happens on failure, leaving significant gaps for a mutation tool.

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 a single sentence of 11 words, front-loaded with the verb and resource, and embeds critical constraints without redundancy. Every word contributes to understanding the tool's purpose and limitations.

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?

The tool has one required parameter and the description covers the core behavior, but the absence of an output schema and annotations means the agent is left uncertain about the return value, error handling, and post-call state. The 'max 20' limit adds some context, but the description does not fully prepare an agent for edge cases like individual URL failures.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes the 'urls' parameter as 'URLs to scrape and index' with 100% coverage, so the baseline is 3. The description adds the 'max 20' constraint, which is crucial for an agent to know before making a call, and clarifies the cumulative purpose of the parameter, elevating the score above baseline.

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 the action 'Add URLs to the RAG corpus' with a specific resource, and the parenthetical 'scrapes and indexes them' clarifies the mechanism. This distinguishes it from read-only tools like search_rag and list_corpus_documents, and the explicit mention of 'RAG corpus' differentiates it from sibling populate tools for sites or YouTube.

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 description implies usage for adding URLs to the RAG corpus but provides no explicit guidance on when to use this tool versus alternatives such as add_source or populate_site. It does not state exclusions or conditions that would make another tool more appropriate, so the context is clear but not fully differentiated.

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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