Digital Gemology: gemology lessons and diamond education

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds valuable context not in the annotations or schema: the result is a set of passages, each tagged with the lesson it came from. It doesn't mention result size or behavior for unknown terms, which keeps it below a 5.

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?

A single sentence that front-loads what the tool returns and uses the parenthetical only for illustrative terms. Slightly dense colon construction but no wasted sentences.

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 one-parameter read tool with rich annotations, the description covers purpose and return shape (passages plus provenance) despite there being no output schema. Only edge-case behavior (no matches found, ambiguous terms) is left unaddressed.

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%, so the baseline is 3. The description improves on the schema's terse 'one or a few words' by giving concrete example terms, which clarifies acceptable granularity (single words or short phrases like 'crown angle').

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+resource: it reports what the lessons say about a single gemology term and what it returns (passages with their source lesson). Concrete example terms ('table', 'crown angle') pin down scope. It doesn't explicitly contrast with search_lessons, so sibling differentiation is left implicit.

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?

Usage is implied by the phrasing 'what the lessons say about one term' – an agent can infer this is for term-definition lookups rather than listing or fetching lessons. But there is no explicit when-to-use, when-not-to-use, or named alternative such as search_lessons.

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

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

Annotations already declare this is a safe, idempotent, non-destructive read in a closed world. The description adds useful behavioral context beyond annotations by specifying the return format and included related content, though it does not discuss error cases or auth requirements.

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?

Two compact sentences with no filler: the first front-loads what is returned and its format, and the second states the required input. Every sentence earns its place.

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 one-parameter read tool with no output schema, the description supplies the return content and acceptable identifiers. It omits explicit sibling routing guidance, so it is strong but not fully 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?

The sole parameter is fully documented in the schema, including an example page path and the title alternative. The description restates accepted identifier forms but adds no syntax or format detail beyond the schema, so the baseline of 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?

States a specific verb/resource: retrieves one lesson in full as Markdown and enumerates included related data such as page, course, quiz, tools, and cuts. It distinguishes itself from list/search siblings by emphasizing a single full lesson, though it does not name those siblings explicitly.

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?

There is no explicit when-to-use/when-not-to-use guidance or named alternative. 'One lesson in full' and the identifier requirement imply this is for detail retrieval after discovery via list/search, but the agent must infer that routing.

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

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

Annotations already declare the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's incremental value is the disclosure that results are ordered and hierarchical, which it does provide. It says nothing about how large the response is or whether the whole tree comes back in one call, which matters for a no-parameter dump.

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?

It is one short sentence, but it is a fragment with no leading verb, and the phrase 'topic hub' is used without definition. Short is good, but the structure does not front-load a clear action for the agent.

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?

With no output schema and no parameters, the description bears full responsibility for explaining what comes back, and it only partially does so: it names courses, topic hubs, lessons, and pages, but not their nesting or volume. An agent knows roughly what to expect but not the response shape or size.

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 takes zero parameters and the schema is a closed empty object, so there is no parameter semantics to explain beyond confirming it takes none. Baseline 4 applies.

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 states a specific resource and shape: all courses and topic hubs together with their lessons and pages, returned in order. It is a sentence fragment rather than a clean verb+resource statement, and it does not distinguish this 'list everything' tool from get_lesson or search_lessons, but the intent is still legible.

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?

There is no when-to-use guidance and no mention of the sibling tools. An agent must infer on its own that this is the full-catalog option versus using search_lessons to find a specific lesson, or get_lesson to fetch one.

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

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuine context beyond that by stating the corpus is free lessons and enumerating the returned fields (title, page, course, summary, quiz), which matters since there is no output schema.

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?

Two sentences, front-loaded with the verb and resource, with the examples and return fields packed in without filler. Every clause earns its place.

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 two-parameter search tool with no output schema, the description covers purpose, query style, and return fields adequately. It says nothing about ranking/relevance behavior or how results relate to the full lesson reachable via get_lesson, a minor but real gap.

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 both parameters are documented, giving a baseline of 3. The description goes further by showing that the query can be a natural-language question rather than just a keyword, which is real semantic value not conveyed by the schema's bare "A topic or a question."

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+resource ("Search ... free gemology lessons") and illustrates it with three concrete example queries, so the tool's function is unmistakable. It doesn't explicitly contrast itself with the siblings get_lesson or explain_term, but 'search' vs 'get'/'explain' is largely self-evident.

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 query examples imply the right usage context (a topical question you want lessons on), which is helpful guidance. However, there is no explicit when-to-use/when-not or pointer to get_lesson for fetching a full lesson, so an agent must infer the boundary with siblings.

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