monitor_the_situation

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

Without annotations, description carries burden. It discloses side effects (calls Firecrawl + LLM, billed) and auth requirements (SF API key). However, it does not detail the return bundle structure or potential error states, leaving some behavioral aspects implied.

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?

Description is a single, well-structured paragraph. First sentence defines purpose, second covers side effects and requirements, third gives usage guidance. No redundancy, every sentence adds value.

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 tool complexity (multi-step, optional components), description is fairly complete: covers actions, optional steps, trade-offs. Return format is not described (no output schema), but context signals indicate no output schema, so burden is on description. Description could be more explicit about the bundle contents.

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%, so the schema already documents all parameters. The description adds context by naming the optional analysis and enrichment steps but does not provide significant new meaning beyond what the schema offers. 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?

Description clearly defines the tool as an end-to-end pipeline for scraping URLs (or search/crawl/map/extract) with optional LLM analysis and prediction market enrichment. It distinguishes itself from the sibling 'enrich_content' by specifying that this tool is for URL ingestion, not for already available text.

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?

Explicitly states when to use: 'Use for scheduled or one-shot URL ingestion' and when not: 'use enrich_content if you already have the text in hand.' Also notes side effects and billing, providing clear context for decision-making.

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