close_lesson_loop

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 irreversibility, four validation checks (ungraded submissions, cognitive update requirement, ref_id validity, Live session receipt requirement), enum enforcement with rejection of unknown kinds, and the optional receipt with historical context. This is exceptionally transparent.

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 a dense wall of text without clear section breaks, containing historical details (dates, retirement rationale) that are not essential for invoking the tool correctly. While every sentence carries information, the length is excessive and could be better structured with bullets or headings. It is not front-loaded with the most critical operational rules.

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 complex tool with nested receipt objects and multiple validation rules, the description is highly complete. It covers all preconditions, error scenarios, validation logic, and even the rationale behind the enum. It notes that receipt carries closure progress, so no separate state-machine query is needed, addressing output expectations despite no output schema.

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?

Input schema has 100% parameter description coverage, so baseline is 3. The description enriches semantics by explaining when receipt is optional, the meaning of each receipt kind, the rules for ref_id, and when no_cognitive_update_reason is needed. It adds value beyond the schema, though much detail is also embedded in the schema.

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's purpose: closing the lesson loop by writing a receipt and setting lesson_progress to closed. It distinguishes itself from siblings like get_lesson_closure_state (read-only status) and grade_exercise (grading) by specifying it is the terminal, irreversible action.

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?

Provides explicit guidance on when to use: after grading and receipt delivery, with a warning that it errors if already closed. It lists preconditions (four server-side checks) and alternatives (grade_exercise for grading, record_post_lesson_evaluation for cognitive updates), and explains when receipt is mandatory (when Live lesson exists) and the escape hatch (no_cognitive_update_reason).

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