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

Beyond the readOnlyHint=false annotation, the description exposes key behavioral details: email delivery is forced to the bound address, destination is ignored for email, webhook requires an https URL and a Pro key, and bind_email must be called first. It also shares the call pattern and the fact that this SUBSCRIBES rather than returns current data. No contradiction with annotations.

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 information-dense but every sentence earns its place: core purpose, free/pro constraints, prerequisite, example call, and explicit alternative. Key behavioral caveats are front-loaded before the example, making it easy for an agent to parse the critical routing decision first.

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 the tool's complexity (two delivery channels, a prerequisite, and pricing constraints), the description covers everything an agent needs: when to use, how to invoke, parameter specifics, and what not to use it for. The presence of an output schema lessens the need to explain return values, and no critical operational context is missing.

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 meaning beyond the schema: it explains that 'destination' is ignored on email, must be https for webhook, and ties 'market' slugs to the outputs of rank_markets/get_market_dcpi_rank. The example invocation also clarifies how the parameters combine in practice.

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?

States a specific verb and resource: 'Subscribe to movement alerts for a DCPI market'. It clearly communicates what triggers the alert ('when its Excess-Power / Constraint score moves') and distinguishes itself from read-only market tools like get_market_dcpi_rank. The use-case framing ('MONITOR markets, not just query them') removes ambiguity about the tool's role among siblings.

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 tells the agent when to use this tool (monitoring future movement) and when not to use it ('Do NOT use to read a market right now (use get_market_dcpi_rank)'). It also names the prerequisite bind_email and differentiates free vs Pro delivery paths. The 'Try:' example gives a concrete invocation, leaving little room for misapplication.

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