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Glama

start_lesson

Begin a persisted chess lesson for a learner on a chosen topic, covering tactics, openings, middlegames, positioning, endgames, or calculation.

Instructions

Start a persisted lesson in tactics, openings, middlegames, positioning, endgames, or calculation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
learner_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it only hints at state creation via "persisted". It does not say whether the lesson requires a prior learner profile, whether it mutates existing state, what happens if a lesson is already active, or whether the call is idempotent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single well-formed sentence with the verb and resource front-loaded and the topic enumeration following. Nothing is wasted, though the enumeration is long enough that the core action could be stated more sharply.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the topic domain is covered. However, for a stateful start tool with no annotations and 0% schema coverage, the description omits session lifecycle, prerequisites, and relationship to the many sibling analysis/lesson tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and both parameters are bare strings, so the description must compensate. It usefully enumerates valid topic values (tactics, openings, middlegames, positioning, endgames, calculation), which is real added meaning, but learner_id remains completely unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ("Start") and resource ("persisted lesson") and enumerates the topic domain, which lets an agent distinguish it from sibling utilities like advance_lesson or create_game_lessons. It is clear but does not explicitly differentiate itself from the closest sibling, start_teaching_session.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no when-to-use guidance, no prerequisites, and never names an alternative such as start_teaching_session, advance_lesson, or create_game_lessons. An agent must infer the selection criteria from the tool name alone.

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