neuron_session_load

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 null return behavior for missing sessions, which is the key behavioral trait. However, it doesn't mention error conditions, side effects, or what shape the returned state takes when a session does exist.

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 short sentences with zero filler. The core action is front-loaded, and the null-return behavior plus intended use are packed efficiently into the second sentence.

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 single-parameter load operation, this is nearly complete: it states the action, the null case, and the decision context. The only gap is describing the return payload for an existing session, but no output schema exists to fill that in.

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 coverage is 100% and the only parameter, session_id, is already described as 'Session identifier'. The description adds nothing beyond the schema, so the baseline 3 applies.

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 states a specific verb and resource ('Load session state') and clarifies the operation is about restoring prior session data. It is clearly distinct from sibling tools like neuron_session_save, neuron_session_delete, and neuron_session_list, though it doesn't explicitly name 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?

The description gives contextual guidance: recipes use this to decide whether to resume or start fresh. This implies the tool is called before beginning a session-dependent workflow, but it doesn't state explicit exclusions or alternatives.

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