aimfp_end

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

Annotations indicate destructiveHint=true. The description adds behavioral details: stops a watchdog process, gathers specific audit data (watchdog state, reminders, files, functions, notes, task state), and returns structured data for AI interpretation. It confirms the destructive action and explains what is gathered, going beyond the annotation.

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, using a few sentences to cover purpose, actions, and key details. It front-loads the purpose ('Session termination orchestrator') and avoids unnecessary words.

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 no parameters and no output schema, the description fully explains what the tool does (end session, gather audit data, stop watchdog) and what it returns (structured audit data for AI to interpret). It provides sufficient context for an AI agent to use the tool correctly.

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 has zero parameters with 100% schema coverage. The description adds no parameter semantics, but none are needed. Baseline for no parameters is 4.

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 it is a session termination orchestrator that gathers audit data. It specifies actions: reading watchdog state, querying files and functions, reading notes and task state, stopping the watchdog, and returning structured data. It distinguishes from siblings by describing its specific orchestration role at session end.

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 clear context: use at session termination. It explicitly says 'No analysis logic — AI determines what is stale or missing,' implying the AI should use the output for analysis. However, it does not explicitly state when not to use or compare to alternative tools like aimfp_init or aimfp_run.

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