checkpoint_session

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

No annotations are provided, so the description carries full burden. It discloses that the tool saves context to graph memory and allows later resumption, but lacks details on side effects (e.g., overwrite behavior, cost, data limits). Adequate but not comprehensive.

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 description is concise (three sentences) and well-structured: action+target, effect, usage scenarios. No redundant information.

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?

Given the simple nature of the tool (2 params, no output schema), the description covers purpose, usage, and parameter semantics. It could mention what the tool returns or how to resume, but overall it is fairly complete.

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 100% – both parameters have descriptions in the schema. The description adds minimal value beyond that (e.g., notes are optional, session_id is unique with an example). Baseline 3 is appropriate.

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 clearly states the tool saves the current AI session as a checkpoint to TokenMizer's graph memory, with explicit use cases like finishing a work session or switching tasks. It distinguishes itself from sibling tool 'resume_session' by focusing on saving rather than resuming.

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 provides explicit when-to-use scenarios (finishing session, switching tasks, long conversations). It lacks explicit when-not-to-use or alternatives, but the given scenarios are sufficiently directive for an AI agent.

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