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

Without annotations, the description carries the transparency burden. It explains the process (simulate each option, rank outcomes), but does not explicitly state side effects, permissions, or that it is a read-only analysis. It also omits any details about output format, which is a notable gap.

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 at three sentences, front-loading the purpose. It uses a compact label 'COMPOSITE' and provides necessary structural input details, though the density might require careful reading.

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 7 parameters, the description covers the core workflow but omits the return value format and the roles of parameters like 'method', 'horizon', and 'period_label'. It is complete enough for a high-level understanding but lacks details needed for full autonomous 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?

With 0% schema coverage, the description compensates well for the most important parameters: 'options' as [{name, inputs}], 'criteria' as [{metric, weight, direction}], and 'template' as a base. However, it does not clarify 'inputs', 'method', 'horizon', or 'period_label', which remain ambiguous.

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 what the tool does: it projects each option as a scenario and ranks them against weighted criteria derived from scenario outcomes. It distinguishes itself from siblings by explicitly stating it 'Combines ScenarioSim + DecisionMatrix', making its composite nature obvious.

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 implies usage for comparing multiple options via simulation and decision matrix, but does not explicitly mention when to use it over alternatives like sim_run or decide_score. It lacks when-not guidance, so usage is only implied.

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