optimize_passives

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

With no annotations, the description fully discloses behavior: it uses a bounded greedy search, is not guaranteed optimal, and explains the points=0 case. It also describes the return format (chosen nodes with gains and metric values).

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 concise: a single paragraph with front-loaded purpose, followed by parameter explanations and a behavioral note. Every sentence adds value with no 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 4 optional parameters, an output schema (exists), and the complexity of a greedy optimization, the description is complete. It covers all parameters, the algorithm, and the return format, enabling correct selection and invocation.

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 add meaning. It explains 'metric' with examples ('TotalDPS', 'Life'), 'points' as number to spend, 'node_type' defaulting to 'Notable', and 'candidates' defaulting to 50. This compensates well for the schema gap, though not exhaustively listing all possible values.

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's purpose: 'Greedily allocate passive points to maximize a stat on the active build.' It specifies a verb ('allocate'), resource ('passive points'), and outcome ('maximize a stat'), distinguishing it from sibling tools like alloc_passive and dealloc_passive.

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 guidance on when to use the tool (to maximize a stat) and explains parameter usage (e.g., points=0 for full budget, metric examples). It does not explicitly state when not to use it, but context is sufficient given the clear purpose.

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