Analyze Outage Impact

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false). The description adds a valuable interpretation caveat by labeling the Pearson correlation as non-causal, but it adds no context on data completeness, missing-hour handling, or the meaning of the default threshold behavior.

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?

One dense sentence that front-loads the core operation (the join), then the outputs, then the caveat. Every clause earns its place, though splitting the causality caveat into its own sentence would improve scannability.

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 analytical intent, output schema, and safety annotations cover the tool's core well. However, high_outage_threshold_mw semantics and default-null behavior are undocumented in both schema and description, leaving an agent to guess what counts as a high-outage hour. For an analysis tool of moderate complexity this is adequate but with clear gaps.

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 0% and the description names no parameters. The schema documents start/end timezone handling but leaves high_outage_threshold_mw with no description; the phrase 'high-outage' is only a weak hint, and the nested request wrapper is never mentioned. The description fails to compensate for the schema gap.

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 uses specific verbs and resources: it 'joins hourly generator outage capacity to Pool Price' and 'reports high-outage versus other-hour price differences plus Pearson correlation.' This makes the analytic purpose clear and distinguishes it from siblings like get_outages or get_pool_prices, though it never names a sibling 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 'as non-causal associations' qualifier is an implied usage constraint, telling the agent how to frame results, but there is no explicit when-to-use guidance, no exclusions, and no routing to alternatives like get_outages for raw outage lists or analyze_market_event for broader event analysis.

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