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

The annotations mark destructiveHint=true and readOnlyHint=false, yet the description only presents a read-only-looking 'derive/computation' profile and never explains what side effect or destruction may occur. It does add useful semantic context about the absence of simulation and the universal claims, but the mutation/destructive behavior is undisclosed. This is not a direct contradiction because the description never claims to be side-effect-free.

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 longer than average but front-loads its main purpose and structures the three result families into clear clauses. The sim_diagnose clarification and the no-simulation caveat earn their place; mild verbosity in the first sentence keeps it from a perfect score.

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?

For a one-parameter tool with no output schema, it explains all three result families, their provenance from the arc structure, and the meaning of deadlock witnesses. That is enough for an agent to know what it will get back. The main gap is the unexplained destructiveHint, which leaves the overall invocation contract incomplete.

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?

The schema already documents id with 100% coverage, so the description adds little about the parameter itself. It does reinforce that id refers to a model and adds meaningful context about 'this model's own initial marking', which helps an agent understand how the invariants are grounded.

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 uses a specific verb, 'Derive', and a precise resource, 'a model's full algebraic invariant structure', then enumerates three concrete output families: P-invariants, T-invariants, and the siphon/trap report. It also differentiates itself from sim_diagnose by explicitly saying this is the same computation, not a lesser copy, so an agent can distinguish it from siblings.

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?

It gives clear context: this is for static algebraic structure, explicitly excludes simulation, and points out the relationship to sim_diagnose's structural fields as an alternative access point. It stops short of a broader decision rule against simulation-oriented siblings, but the boundary is clear enough.

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