list_equations

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

No annotations exist, so the description carries the full burden. It does add real behavioral value by explaining the `broken` flag (an equation whose dimension/variable is gone, left by delete_feature) and `automatic_solve_order=False` (solver warns/lags a rebuild). However, it never explicitly states this is a read-only, side-effect-free operation, which is a notable omission for a tool with zero annotation coverage.

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 purpose is front-loaded, which is good, but the second half is dense and hard to parse ('one above the line that sets its variable then warns and lags a rebuild'). The jargon-heavy explanation of automatic_solve_order could be tightened. It is not wasteful in length but loses clarity.

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 the returned data, and it does enumerate the returned fields plus the meaning of the `broken` and `automatic_solve_order` states. For a zero-parameter list tool this is close to complete, though the ambiguous automatic_solve_order prose leaves some interpretation to the agent.

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 tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to disambiguate, and it correctly spends no space on parameter detail.

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 ('List the equations and global variables') and even enumerates the fields returned (index, equation, name it sets, value, global). It is clearly distinguishable from set_equation, delete_equation, and list_dimensions by resource. It stops short of explicitly naming which sibling to prefer, so not a 5.

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?

Usage is only implied: this is an inspection/read tool, and the notes reference delete_equation and set_equation as related operations. There is no explicit 'use this when...' or 'do not use this for...' statement, so the agent must infer the when-to-use context from the field semantics.

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