scrape_profile

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

With no annotations, the description carries the disclosure burden. It reveals that the tool performs an external Apify scrape, writes to the database, and requires APIFY_API_TOKEN in the .env file. It does not discuss rate limits, latency, or whether existing records are overwritten, but the key side effects and prerequisites are disclosed.

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 tightly organized: purpose sentence, usage guidance, environment requirement, then parameter details. Every sentence earns its place and there is no 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?

It covers purpose, use cases, authentication, and all parameter semantics in a compact form. The only slight ambiguity is the line 'Works for profiles NOT yet in the database' followed by a use case for existing accounts, but the later sentence resolves the intent. An output schema exists, so return-value details are not required.

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 description coverage is 0%, so the description must compensate. It fully documents url with realistic examples and max_posts with default and maximum values, adding meaning far beyond the raw 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 opens with a specific verb and resource: scrapes fresh LinkedIn posts and stores them in the database. It distinguishes itself from siblings by emphasizing it works for profiles not returned by list_accounts and by targeting posts rather than people or comments.

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 says when to use the tool: when list_accounts() does not return the account, or when fresh posts are needed for an existing account. It does not name exclusions or alternatives like get_posts/list_posts for reading already-stored posts, so it stops short of full alternative routing.

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