set_alert_policy

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

With no annotations, the description carries full burden. It discloses that the tool sets policies, supports glob patterns, and includes parameters like muted, min_pct_change, min_usd_change. However, it does not specify whether it overwrites existing policies, requires specific permissions, or if the operation is reversible, leaving some behavioral ambiguity.

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 well-structured, starting with the purpose, followed by usage guidelines, parameter details, and examples. It is concise with no redundant sentences; every sentence adds value. Front-loading with the core action and use cases aids quick comprehension.

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 no output schema and the tool's mutation nature, the description covers all necessary aspects: what it does, when to use it, parameter semantics, and examples. It is complete and leaves no major gaps for an AI agent to invoke it 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 coverage is 0%, so the description must explain all parameters. It includes an 'Args:' section with clear explanations for each parameter (provider, service_pattern, muted, min_pct_change, min_usd_change, note). Examples further clarify usage, such as glob patterns and effect of each parameter.

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 clearly states the tool sets a custom alert policy for anomaly detection on a specific provider or service. It distinguishes from sibling tools like delete_alert_policy and list_alert_policies by focusing on configuration. The specific use cases (muting noisy services, raising thresholds, setting minimum dollar delta) further clarify purpose.

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 explicitly lists scenarios for using the tool under 'Use this to:' with concrete examples. It implies when to use (muting, threshold adjustment) but does not explicitly state when not to use or mention alternatives like acknowledging anomalies. The examples guide usage effectively.

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