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

Beyond readOnlyHint=true, the description discloses the payload shape (primary algorithm plus alternates, sources, finger-trick notes) and a meaningful trust property — every algorithm is validated by app/cube/scripts/audit-algorithms.mjs before data lands. It does not cover pagination behavior or the default/max limit handling, which would round this out.

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?

Four sentences, front-loaded with what the sets are and their sizes, then payload shape, then verification, then filtering. Every sentence carries information; the audit-script sentence is the longest and borders on promotional, but it does establish data quality, which is relevant to an agent deciding whether to trust the output.

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?

There is no output schema, so the description must explain return values — and it does: each case returns the primary algorithm plus alternates, sources, and finger-trick notes, or the set's structure and levels when unfiltered. Combined with complete schema documentation for the four parameters, an agent has everything needed to call it 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?

Schema coverage is 100%, so the baseline is 3, and the description earns an increment by explaining the omitted-filter case ('omit both for the set's structure and levels') — semantics the schema does not convey. The set enum values and group examples are already documented in the schema, so no further credit is due there.

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?

States a specific verb and resource — retrieving Rubik's cube last-layer algorithm sets (OLL 57, PLL 21, two-look subsets, ZBLL) used by the K2 cube trainer — plus what each case contains. The scope is unmistakable, though it never names a sibling (e.g. explain_k2_algorithm) to contrast against, so differentiation is inferred rather than stated.

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 final sentence gives concrete selection guidance between the filters: 'Filter by `case_id` or `group`; omit both for the set's structure and levels.' That is useful when-to-use-a-parameter guidance, but there is no statement of when to prefer this tool over siblings like explain_k2_algorithm, nor any exclusions or prerequisites.

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