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

Goes well beyond the annotations: nothing is recalculated, factors are read from the engine that produced the assessment, results are stored beside unchanged characterized results, re-application refreshes (consistent with idempotentHint), partial category coverage is possible, and it cites the ISO 14044 restriction on public comparative assertions. This is unusually rich behavioral disclosure.

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?

Front-loads the core action and keeps every sentence substantive, but it is dense with several distinct topics (storage semantics, refresh, partial coverage, ISO caveat) that could be tightened. No filler sentences, so it stays efficient.

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?

With no output schema, the description carries the burden of explaining what gets produced: normalized/weighted results per category plus a single score, stored alongside unchanged characterized results, with omitted categories named. An agent has everything needed to invoke and interpret the call.

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 100%, so the baseline is 3, but the description adds real meaning: ref is an a<N> in the named workspace, nw_set must match one of the method's sets (exact or unique part), and workspace is mandatory per call because connections are shared. It reinforces and contextualizes the schema rather than merely repeating it.

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 precise verb+resource: applying a normalization/weighting set to a saved assessment. It explicitly distinguishes itself from lca_compare_assessments (which uses nw_set only to compare assessments all carrying the same set), so an agent can route correctly without opening schemas.

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?

Gives explicit when-to-use conditions: apply to a saved assessment, unknown set names are refused, re-applying refreshes rather than duplicates, and comparison of sets belongs to lca_compare_assessments. Alternatives and preconditions are named, not implied.

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