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

With no annotations, the description carries the full burden and delivers extensively. It discloses operational behavior (on-demand execution, no background scheduler), constraints (max 20 keywords, free pilot, no API key), output characteristics (per-keyword counts, snippet context, Ed25519-signed deliverables), privacy handling (in-memory processing, no logging/training), state lifecycle (wiped on restart), and fair-use limits (20 tasks/day, availability endpoint). This is far beyond typical descriptions.

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 long and detailed, with many sentences covering privacy, fair use, and signing. While every sentence adds value, it is not concise; the core functionality is front-loaded but the additional context might overwhelm an agent. The structure is logical (what, how, constraints, privacy, fair use), but the length makes it less efficient than necessary.

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?

The tool is moderately complex (nested object, action enum, multiple optional parameters) and there is no output schema. The description explains the output in general terms ('reports per-keyword match counts with snippet context') but does not detail the response structure, format, or error handling. It covers many behavioral aspects but leaves out precise return format, which is important for an agent to parse results correctly.

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 50% (only quote_id is described in schema). The description adds meaning for the 'input' object: it explains the two actions (register/check) and that keywords are the focus, and mentions URL implicitly. It does not explain tripwire_id or label in detail, but the description's context helps an agent infer their roles. It partially compensates for the schema gap but does not fully specify every parameter's semantics.

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 states a specific action ('watch a public page or feed for keywords'), the resource (public pages/feeds), and the outcome (per-keyword match counts with snippet context). It clearly distinguishes this from the sibling tools (citation_audit, claim_verification, etc.) by its unique focus on keyword monitoring and on-demand checks, though it does not name them explicitly.

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 explains the core usage pattern ('Register the watch once, then check on demand') and clarifies that checks run only when called ('no background scheduler'). It also notes what the tool does not do ('reports keyword presence, not news judgement'), which helps set expectations. However, it does not mention alternative tools or explicitly state when to use this versus others, leaving some inference to the agent.

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