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

With no annotations, the description carries the full burden, and it does disclose the return shape (complete taxonomy structure with bilingual Chinese/English names) and implicitly that this is a read-only enumeration. It omits any note on result size, pagination, or caching, which is the remaining behavioral gap.

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?

Purpose is front-loaded in the first sentence, usage follows in the last. The bilingual duplication roughly doubles the length, which is redundant for an English-only reader, but the pairing is presumably intentional and neither version contains filler.

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 zero-parameter, no-output-schema list tool with no annotations, the description supplies what an agent needs: what comes back, in what languages, and when to call it. Only secondary details like response size or ordering are absent, which is acceptable here.

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, so there is no parameter semantics to document and the baseline is 4. The description correctly implies the call is unfiltered and takes no arguments.

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?

Specific verb 'List' plus the exact resources returned (categories, subcategories, series, forms) in the SciGlyph library, so the agent knows precisely what it gets. It partially differentiates from siblings by implying a survey-first role, but does not explicitly contrast with sciglyph_library_info or sciglyph_list_by_category, which sound closely related.

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?

Gives clear sequencing guidance: 'Use this tool first to understand the library's organization before searching for specific assets,' which ties it to the search workflow. It stops short of stating when NOT to use it or naming search_assets as the explicit alternative in the English text.

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?

No annotations are provided, so the description carries the full burden. It usefully discloses the shape of the return (bilingual name, category, file path, SVG URL) in the absence of an output schema, but says nothing about behavior on a missing/invalid ID, auth needs, or whether it is a pure read.

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?

Front-loaded with the core action and kept to two mirrored sentences. The English/Chinese duplication doubles the token cost without adding new information, which is a mild waste but consistent with a bilingual tool.

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 simple single-parameter lookup, the description covers purpose and return contents, and the schema covers the input. The remaining gap is error/not-found behavior, which matters little for a read-only detail fetch.

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% and the single assetId parameter is fully documented in the schema with format examples. The description adds nothing beyond that, so the baseline of 3 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?

States a specific verb and resource ('Get detailed information about a specific asset by its ID') and enumerates the returned fields. This clearly differentiates it from search/list siblings in practice, though it never names an alternative tool 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?

The phrase 'by its ID' implies the precondition that the caller already has an assetId, which is usable context. However, there is no statement of when to choose this over sciglyph_search_assets or sciglyph_get_url, and no exclusions or downstream-use guidance.

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?

No annotations are provided, so the description carries the burden. 'Construct' implies a pure, side-effect-free computation rather than a network fetch, which is useful, but it says nothing about the return shape (bare URL string vs object), whether any validation or error is returned for a nonexistent path, or any auth/rate-limit behavior.

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 front-loaded sentences, each doing real work — first the action, then the use condition. The size is inflated only by the bilingual mirroring convention, not by redundancy in substance.

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 simple three-parameter URL composition tool with no output schema and full schema coverage, the description covers what it does and when to reach for it. The one remaining gap is the exact return value/error behavior, which matters slightly for a constructor that can be given a bad path.

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% with all three required params documented with formats and examples, so the baseline is 3. The description adds the mental model that these are 'path components' composed into a URL, but nothing beyond that mapping.

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 artifact — 'Construct the direct SVG URL' — and names the exact inputs (category, subcategory, filename). The clause 'but the asset is not in the indexed metadata' implicitly separates it from search_assets/get_asset, so an agent can route correctly without opening a schema.

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?

Gives a clear triggering condition: use it when you already know the exact category, subcategory, and filename and the asset is not indexed. It doesn't explicitly name the alternative tools to fall back on when the asset IS indexed, but the negative condition is stated plainly.

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?

No annotations are provided, so the description carries the full burden. It discloses the payload type (usage examples for embedding) and that examples are context-specific, but says nothing about the response format (code blocks vs prose), whether output is static, or any auth/rate considerations. Adequate but thin for an unannotated tool.

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 front-loaded sentences that state purpose and scope with no filler. The bilingual duplication is mildly redundant but appears to be a service convention rather than padding.

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 simple, side-effect-free retrieval tool with one optional parameter and no output schema, the description conveys what is returned and the embedding contexts covered. Only the exact return shape (snippet format) is unspecified, a minor 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 description coverage is 100%, so the single optional assetId parameter is already fully documented in the schema, including the fallback-to-sample behavior. The description adds no additional meaning about the parameter, so the baseline 3 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 verb and resource ('Get usage examples showing how to embed SciGlyph SVG assets') and names the concrete contexts (Markdown, HTML). It is clearly distinct from sibling retrieval tools like get_asset or get_url, though it never names 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?

Usage is implied: call this when you need embedding snippets. There is no explicit when-to-use vs alternatives guidance, no mention of how this differs from sciglyph_get_url or sciglyph_get_asset, and no prerequisites or exclusions stated.

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?

No annotations are provided, so the description carries the full burden. It discloses the shape of the response (version, license, count, author, URL), which implies a safe, non-mutating read, but it says nothing about auth requirements, caching, or whether the call is expensive. Reasonable but thin for a zero-annotation tool.

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, front-loaded sentence with no preamble; the bilingual Chinese rendering duplicates the same content but is presumably required for this library's i18n convention, so it is not wasted prose in context.

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 is the only source of return-value information, and it lists the five key fields, which is sufficient for an agent to decide whether to call it. Only the absence of usage routing keeps it from being 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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The enumerated return fields actually add value the empty schema cannot express.

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 ('Get general information about the SciGlyph library') and enumerates the returned fields: version, license, total assets, author, URL. This is clearly distinguishable from the data-retrieval siblings, though the description never names or contrasts them 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?

Usage is implied by the resource name — call this for library-level metadata rather than asset-level data — but there is no explicit when-to-use, when-not-to-use, or pointer to alternatives among the six sibling tools. Adequate but leaves routing to inference.

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?

No annotations are provided, so the description carries the full behavioral burden. It does not state that this is a read-only/safe operation, nor does it describe pagination, ordering, or result shape for the limit-bounded listing. It only restates the listing scope.

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 short, front-loaded sentences (purpose then usage), mirrored bilingually with no filler. Efficient, though the bilingual duplication doubles the token footprint without adding new information.

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 simple, annotation-free read/list tool with a fully documented 3-parameter schema and no output schema, the description covers purpose and basic usage adequately. The main residual gap is pagination/ordering behavior, which is minor for a browse operation.

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 category, subcategory, and limit are all fully documented in the schema, including the default and the 'omit subcategory' behavior. The description adds no parameter detail beyond what the schema already provides, so baseline 3 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 verb (list/browse) and resource (assets under a category or subcategory) with scope qualifiers. It is clearly distinguishable from get_asset or browse_categories, though the distinction from search_assets is only implied by 'known category' 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?

'Use this to browse assets within a known category' gives an implied when-to-use condition, but it never names the alternatives (search_assets for unknown categories, browse_categories for discovery) or states exclusions. Usage is inferable but not explicit.

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?

No annotations are provided, so the description carries the full burden. It does disclose the return content (bilingual names, asset paths, direct SVG URLs), which is a genuine behavioral detail, but it says nothing about result ordering, truncation, or how the default limit interacts with a broad query.

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 capability, filters, and return shape are front-loaded in the opening clause of each language block. The full bilingual duplication doubles the length, though that appears intentional for a Chinese/English audience and no sentence is wasted padding.

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, the description appropriately explains what results contain (bilingual names, paths, SVG URLs), and all six optional filters are covered by the schema. Only the absence of guidance about broad-vs-narrow queries and result limits keeps it short of full completeness.

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%, and each parameter carries inline documentation including enumerated example values. The description only restates the filter axes (category, subcategory, series, form) without adding semantics beyond the schema, so the baseline of 3 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?

States a specific verb and resource ('Search for scientific illustration assets in the SciGlyph library by keyword') and names the supported filter axes. It does not explicitly distinguish itself from siblings like sciglyph_list_by_category or sciglyph_browse_categories, but the keyword-based framing is a reasonable implicit differentiator.

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?

It notes that filtering by category/subcategory/series/form is optional, and the schema adds that an omitted query returns everything matching the filters, which implies usage. However nothing states when to prefer this over sciglyph_list_by_category, sciglyph_browse_categories, or sciglyph_get_asset.

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