run_project_tests

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

With no annotations, the description carries the full burden. It usefully discloses the auto-detection behavior, the custom_command override, and that stdout/stderr are returned, but it says nothing about execution environment, timeouts, truncation, or the fact that this executes arbitrary commands with potential side effects.

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?

Three short sentences, front-loaded with the core action, and every sentence adds distinct information (what it does, why to use it, how the parameter changes behavior). No waste.

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?

The presence of an output schema means return values need not be explained, and the single optional parameter is covered. But for an execution tool with zero annotation coverage, the absence of any safety, timeout, or environment context leaves a meaningful gap.

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 0%, so the description must compensate, and it does: it explains that custom_command replaces auto-detection with the given command line. It does not clarify expected format (shell string, args, quoting), so it falls short of fully documenting the parameter.

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+resource: it auto-detects and runs the project's test suite and returns stdout/stderr. It is clearly distinct from the generation-oriented siblings (generate_*), though it never explicitly names or contrasts them.

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?

'Can be used by the AI to verify correct behavior of generated code' gives one implied usage context, which is a reasonable hint. However there is no when-not guidance, no mention of alternatives, and no prerequisites (e.g., project must be initialized, tests must exist).

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