flow.read_memory

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

No annotations are provided, so the description carries the full burden. It communicates a read operation, but it does not disclose what the tool returns, whether it reads all recorded memory or only the latest state, whether it has side effects, or any ordering/filtering behavior.

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?

A single sentence with no filler. The core action and resource are front-loaded, and every word contributes to the tool's meaning.

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 read tool, the description is minimally viable, but it lacks return-format details and any guidance on how to interpret or consume the read results. The low complexity keeps this from being lower, but the missing behavioral context prevents a higher score.

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 input schema is empty and parameter coverage is effectively 100%, so there are no parameter semantics for the description to clarify. The zero-parameter design makes this dimension straightforward.

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 ('Read') and identifies a clear resource ('recorded flow checkpoints, runs, and code-flow analyses'). This distinguishes it from the flow.record_* and flow.replay_* siblings, though it does not explicitly name an alternative.

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?

The description gives no explicit guidance on when to use this tool versus alternatives such as flow.plan_replay, flow.replay_to_checkpoint, or loop.read_iterations. It implies a retrieval use case but does not state exclusions or prefer conditions.

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