get_ai_kpis

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

No annotations provided, so description carries full burden. It describes the tool's behavior: runs all metrics, returns savings estimates and remediation advice. It mentions required optional parameters. No contradictory or missing behavioral info.

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 with a bulleted list of KPIs, clear parameter documentation, and relevant examples. It is front-loaded with purpose and every sentence provides value without redundancy.

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, the description sufficiently explains the output (list of KPIs with savings estimates and remediation advice). It covers all necessary aspects for an AI agent to understand and invoke the tool 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 has 0% description coverage, but the description thoroughly explains both parameters: days (lookback window, default 30) and infra_total_usd (optional, for AI-vs-infra ratio). This adds significant meaning beyond the schema's type and default.

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 'Full AI cost health dashboard with actionable KPIs' and enumerates all included metrics. It distinguishes itself from sibling tools like get_ai_spend_monitor by being a comprehensive one-call dashboard.

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 provides clear usage context with examples covering various questions. It says 'Runs all AI cost health metrics in one call', implying it's for comprehensive overview. However, it lacks explicit when-not-to-use or alternative tool references.

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