facts

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

With no annotations provided, the description carries the full transparency burden. It explains that the tool returns everything currently believed, grouped, with fact ids. As a 'list' operation, read-only behavior is strongly implied, and no side-effect or permission concerns are suggested.

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?

Two tight sentences: the first states the action and output format, the second gives the intended use. Every clause earns its place with no redundancy or fluff.

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 zero-parameter tool with no output schema, the description is nearly complete: it names the action, the data scope, output grouping, fact ids, and the use case. It does not mention pagination or potential large result sizes, but that is a minor omission for a simple audit-listing tool.

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 the input schema fully covers parameter semantics. The description adds no parameter-specific meaning, but none is needed; the baseline of 4 applies because there is no parameter burden to carry.

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 ('List') and a clear resource ('everything currently believed about this project'), and indicates the output is grouped with fact ids. It clearly implies a comprehensive audit listing, but it does not explicitly name or contrast sibling tools like recall.

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 provides an explicit use case: 'Use to review or audit the memory.' This gives clear context for when to call the tool, though it does not mention when not to use it or point to alternatives.

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