generate_rca

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

With no annotations, the description carries the full burden. It does disclose a genuinely important trait – it returns a structured prompt the host LLM completes, rather than the finished document itself – which is valuable beyond structured fields. However, it omits permission requirements, how optional params (8 of 9 are optional) are handled when absent, and any limits.

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?

Two sentences, front-loaded with the core action, with no filler. The second sentence is long but each listed section earns its place by telling the agent what the generated document will contain.

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?

No output schema exists, so the description must characterize the return value – and it does, describing the structured prompt and its component sections. For a 9-parameter generation tool this is largely complete, with only optional-parameter behavior left unaddressed.

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 89%, so the schema already documents nearly every parameter. The description lists the output sections (summary, timeline, root cause, impact, resolution, corrective actions, preventive measures, lessons learned), which loosely maps to the input fields but adds little syntax or format meaning beyond the schema.

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 ("Generate") and resource ("detailed Root Cause Analysis report") scoped to "a production incident," and no sibling tool overlaps with this capability, so an agent can distinguish it immediately.

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 context "for a production incident" implies post-incident usage, but the description never states when to reach for this versus e.g. analyze_bug or jira_create_issue, nor any preconditions or exclusions. Usage is inferable but not guided.

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