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

With no annotations provided, the description carries the full burden and does substantial work: it declares read-only, no-auth behavior and enumerates the returned verdict structure (overall status, per-axis rulings with reasons, three-layer attribution L1→L2→L3). It does not discuss failure modes, error responses, or cost/latency, which keeps it short of a 5 for a no-annotation tool.

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-loaded with a bracketed scope header that immediately frames the tool, then the verb/resource, then usage examples, then the critical caveat. It is dense with parentheticals and layer notation, but each clause carries distinct information (outputs, use cases, dimension warning) rather than repetition.

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?

There is no output schema, so the description must explain return values itself — and it does, enumerating overall verdict, per-axis adjudication with reasons, and the three-layer composed attribution. Combined with the explicit scope/caliber caveat versus check_compatibility, an agent has everything needed to call it correctly.

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 100%, so the schema already documents both parameters, including the component1_id format hint and the search_components prerequisite. The description's only added semantic is that omitting component2_id returns library-level aggregation, which the schema states verbatim, so it adds no meaning beyond the structured fields.

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 and resource: it queries the RoboParts three-axis composition verdict (mechanical/electrical/signal), naming exactly which outputs it produces (overall composed/type_error/unknown, per-axis verdicts, attribution layers). It also explicitly distinguishes itself from the sibling check_compatibility by dimension, so an agent can tell them apart without inspecting 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?

Explicitly lists the questions it answers ("why was this pair judged type_error", "which pairs can actually be assembled", "is composed=0 a data gap or a relation-type issue") and names the alternative tool plus the condition under which its dimension differs (signal role complementarity vs. check_compatibility's protocol bus + ROS2). It even warns the two outputs must not be mixed, which is a clear when-not-to-substitute rule.

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