MGS Toolbox

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 implies a read-only retrieval operation (a vocabulary list) but does not disclose the return format (e.g., array vs. object), whether results are sorted, or any other behavioral details.

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 single, front-loaded sentence that immediately communicates the core purpose (vocabulary of track filters) and then enumerates the specific categories included. There is no fluff or redundant phrasing.

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 tool with no output schema and no annotations, the description is largely complete — it states what the tool provides and the scope of that content. The only missing detail is the expected output structure, which is minor given the tool's simplicity.

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 has zero parameters (empty input schema), so the baseline of 4 applies. There are no parameters for the description to explain, and the description correctly focuses on the payload rather than inputs.

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 identifies the resource (track filter vocabulary) and scope (every genre, mood, era, and keyword in use). It distinguishes itself from sibling tools like search_tracks or get_entry by focusing on the taxonomy rather than individual records, though it uses a noun phrase instead of an explicit verb.

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 description implies usage — you would call this when you need the list of valid genres, moods, eras, or keywords for building track filters. However, it does not explicitly contrast with alternatives like list_facets or search_tracks, leaving the decision 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 must carry the full behavioral burden. It does disclose that the output is HTML sections with titles, which is useful. However, it does not state whether the operation is read-only, mention the optional lang parameter behavior (e.g., default is 'en'), or describe any side effects. Given the lack of annotations, more transparency is expected.

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 single, compact sentence that front-loads the primary purpose and lists the content areas. It is efficient with no redundant words. However, it could be slightly more explicit about the action (e.g., 'returns' or 'retrieves'), which would strengthen clarity without adding bulk.

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 tool with one optional parameter, the description is reasonably complete: it states what is returned and the output format. It does not mention default language behavior or error cases, but these are not critical given the schema. The absence of an output schema is partially mitigated by describing the HTML sections. Still, it could benefit from stating that lang is optional and defaulting to 'en'.

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 input schema already documents the lang parameter with a clear description and enum values, achieving 100% coverage. The description does not add any additional meaning about parameters. Since schema coverage is high, a baseline score of 3 is appropriate; the description neither enhances nor detracts from parameter understanding.

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 function: returning the crafting system rules (characters, essences, extraction, brewing, gem cutting, socketing) formatted as titled HTML sections. It distinguishes itself from sibling tools, which deal with entries, tracks, and audio taxonomy, by focusing on crafting rules.

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?

No explicit guidance on when to use this tool versus alternatives. While sibling tools are clearly different in scope, the description does not mention any prerequisites, use cases, or exclusions. The agent must infer that this is the only tool for crafting rules, which is not 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 transparently lists the output contents (properties, lore, page url, embed_url) and gives no indication of side effects, implying a read-only operation. It does not explicitly state read-only, but the wording is consistent with a safe fetch.

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 single concise sentence that efficiently conveys the purpose, target item types, ID source, and output fields. No unnecessary words or redundancy.

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?

The description provides context by referencing the sibling tools that supply the ID and names the output fields, which helps the agent understand the tool's role. Since there is no output schema, this enumeration of contents is adequate. It could be slightly richer by noting the language options, but that is covered in the parameters.

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 schema already provides clear descriptions for all three parameters, giving 100% coverage. The tool description adds contextual meaning by naming the allowed categories (metal, mineral, ingredient, potion, gem) and tying the id to the source tools, though it does not specifically mention the 'lang' parameter beyond 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 that the tool retrieves the full data of a single entry (metal, mineral, ingredient, potion, or gem) by its ID, and explicitly references where the ID comes from (search_encyclopedia or list_entries). This distinguishes it from sibling tools that list or search entries.

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 description implies when to use it (after obtaining an ID from a search or list) and indirectly contrasts with other tools. However, it does not explicitly state when not to use it, such as for random selection or batch retrieval, though sibling tool names hint at those alternatives.

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. It adds that the tool returns 'published alternative versions', implying filtering by publication status and inclusion of variants, but does not disclose error behavior, permissions, or response structure.

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 waste. It states the core function and key scoping constraint efficiently.

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 get tool, the description covers the basics, but lacks details on response format, error cases, and what 'alternative versions' entails. Given no output schema and no annotations, it is somewhat incomplete.

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 schema has one parameter 'id' with no description (0% coverage). The description clarifies that 'id' can be either an id or a slug, adding meaning beyond the plain string type 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 uses a specific verb 'get' with resource 'track', and specifies the identifier types (id or slug) and the inclusion of alternative versions, clearly distinguishing it from sibling tools like search_tracks and random_track.

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 implies usage when you have an id or slug, but does not explicitly state when to choose this over search_tracks or random_track. No exclusions or alternative conditions are mentioned.

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?

With no annotations, the description carries the burden. It discloses that only published albums are included and enumerates the fields returned (track count, page URL, embeddable player URL), which is useful. It does not mention ordering, default pagination, or any side effects, but for a read-only list tool the disclosed behavior is meaningful.

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 immediately names the returned resource class and the three key output fields. There is no filler or repetition.

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?

The tool is simple, but there is no output schema and no annotations, so the description must compensate. It states return fields, but omits pagination semantics, the meaning of 'published,' and how this tool relates to nearby siblings. An agent could call it, but would be guessing about limit/offset behavior.

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 0% and the description does not mention limit or offset at all. An agent cannot learn from this definition what limit/offset control, whether they are required, or how pagination behaves. The description adds no parameter meaning beyond the raw type and bounds 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 title 'List albums' provides a specific verb + resource, and the description sharpens it: only 'Published albums' are returned, with track count, page URL, and embeddable player URL. This distinguishes the tool from sibling list_entries, list_composers, and search_tracks without needing to inspect schemas.

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?

No guidance is given about when to choose list_albums over siblings such as search_tracks, list_entries, or get_entry. The description only says it returns published albums; it does not state exclusions, prerequisites, or a selection rule.

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?

Discloses output scope, ordering, and included field (page URL). No annotations exist, so the description carries the burden and covers the main behavioral aspects, though pagination or result limits are not mentioned.

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?

Single concise sentence with no redundant wording. Front-loads the action and resource, then specifies scope, ordering, and output field efficiently.

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 parameters and no output schema, the description adequately conveys what the tool returns and in what order. Minor omissions like empty-result behavior or potential size are not critical for a simple list tool.

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 has no parameters, so parameter-specific guidance is irrelevant. Schema coverage is effectively complete, and the description adds no parameter semantics because none exist.

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 ('list') and resource ('composers') with clear scope: every composer with published tracks, ordered by prolificness, including page URL. Distinct from sibling tools by naming and scope.

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?

Implies usage when you need all composers with published tracks, but does not explicitly explain when to choose this over sibling tools like list_entries or search_encyclopedia, nor provide exclusions or alternatives.

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 must carry the full burden of disclosing behavior. It mentions 'page' and filtering but does not describe the exact output format (e.g., list of entries, pagination metadata, error behavior). It also does not explicitly state that it is read-only, though the name and context imply it. This lack of detail limits transparency.

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 two sentences with three concrete examples and a clear instruction about combining with q. No redundant words; it is efficient and to the point.

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?

No output schema is provided, so the description should explain what the tool returns. It only says 'page of one catalogue' which is vague. It does not describe the structure of entries or whether pagination information is included. Given the lack of an output schema, this is a significant 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?

Kind, lang, and filters are described in the schema, and q is clarified as a name search in the description text. However, limit and offset have no description, and filters' allowed fields are only listed indirectly via the schema's description. The overall coverage is moderate, leaving users to guess the effect of offset and the exact matching rules for filters.

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 that the tool lists a page of a catalogue with filters and gives concrete example queries (e.g., 'cubic and gem-quality' minerals) that illustrate the intended use. It does not explicitly name sibling tools, but the examples make the purpose distinguishable from list_facets (which lists filter values) and get_entry (which fetches a single entry).

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 provides three example user intents and instructs to combine with q for a name search inside the filter, offering practical guidance on when to apply the tool. However, it does not contrast with alternatives like search_encyclopedia or get_entry, so the guidance is implicit rather than 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?

With no annotations, the description carries the full burden. It discloses that the tool returns distinct values with entry counts, implying a non-mutating read operation, but it does not explicitly state it is read-only, mention any limits, or describe the return format in detail. This is acceptable but leaves some implicit behavior undisclosed.

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 single, front-loaded sentence with no redundancy. Every word contributes to explaining the tool's purpose, making it an efficient and well-structured definition.

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?

Given the simplicity (one enum parameter, no output schema), the description sufficiently explains what the tool does and what it returns. It lacks details about edge cases or pagination, but for a facet-list tool this is likely sufficient. It is complete enough for an agent 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?

The schema covers the single parameter 'kind' with an enum and description. The tool description adds no additional meaning beyond that, so the baseline of 3 is appropriate because the schema handles the semantics completely.

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 action (list) and the resource (distinct values of filterable fields of a catalogue) with examples. It is specific enough to distinguish from siblings like list_entries, which would list catalogue entries rather than facet values.

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?

No guidance is given on when to use this tool versus alternatives such as list_entries or search_encyclopedia. The description only explains what it does, not when an agent should choose it. There are no exclusions or conditions for use.

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 full responsibility. It states behavior (random selection, filters applied) but omits critical details such as what happens when no entries match, whether the selection is uniformly random, and whether it modifies any state. The description is too terse to fully inform the agent about edge cases.

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 single, concise sentence with illustrative examples, making it easy to read. It avoids unnecessary verbosity. The structure is acceptable for a simple tool, though a bulleted list of parameters could be more organized.

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?

The description does not explain what an 'entry' is, how kind and filters interact, or that kind is required. It does not mention output format or error behavior. Given the nested filters object and the need to understand catalogue-specific fields, the description leaves too much to the schema alone.

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 descriptions cover 100% of parameters with detailed explanations, including the filters format and examples. The description text adds little beyond the schema, only referencing filters. Since schema coverage is high, the baseline is 3; the description does not degrade or elevate this.

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 action (return one entry at random) and the resource (entry), and provides concrete examples of use cases (loot tables, mineral of the day). It distinguishes from siblings like random_track by focusing on entries, though it does not explicitly name alternatives. The title and name reinforce the purpose.

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 description gives examples of when to use the tool (e.g., for a loot table) but does not explicitly state when to prefer this over list_entries, search_encyclopedia, or random_track. It lacks guidance on alternative tools or exclusions, leaving the agent to infer from context.

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?

The description accurately states behavior but omits details such as return format, error handling when no tracks match, and confirmation that it is a read-only operation. Given no annotations, the description carries the burden and only partially meets it.

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 single concise sentence with no redundant words, making it easy to parse.

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?

The description is minimal and lacks an output schema or return-structure details. It also doesn't mention potential error responses. However, within the context of sibling tools, a 'track' object is likely understood, so completeness is adequate but not full.

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 schema covers all 10 parameters with descriptions. The tool description adds no additional parameter semantics. The descriptions are clear individually, but the description does not clarify how multiple filters are combined (e.g., AND vs OR). Baseline 3 applies due to high schema coverage.

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 returns a random published track filtered by criteria. It distinguishes from sibling tools like search_tracks (search) and random_entry (random encyclopedia entry) by specifying 'published track' and 'matching the filters'.

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 description provides no guidance on when to choose this tool over alternatives. It does not mention use cases or conditions, nor does it reference sibling tools.

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?

The description details search behavior: case- and accent-insensitive matching, result ordering (exact names first, then prefixes, then substrings), and inclusion of aliases. It also lists the return fields. This gives a good understanding of what to expect, though it does not explicitly state read-only behavior (which is implied but not stated).

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 two sentences long and packs all necessary information without redundancy. It efficiently communicates the search scope, behavior, and output format, with no wasted words.

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?

The description fully covers what an agent needs to know: what is searched, how the search behaves, and what the response contains. It also appropriately directs to 'get_entry' for full details, making the tool's role in a larger workflow clear. No output schema is needed given the explicit field list.

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 description adds useful context for the 'q' parameter by explaining case-insensitivity and ordering, but does not elaborate on 'kind', 'lang', or 'limit'. Since the schema already provides descriptions for 'kind' and 'lang', the marginal add is limited. 'limit' lacks any description in the schema, and the tool description does not clarify it either.

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 that the tool finds encyclopedia entries by name across specific categories (metals, minerals, alchemical ingredients, potions, gems). The verb 'Find' explicitly indicates the search action, and the scope is well-defined, leaving no ambiguity about the tool's purpose.

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 description provides a pointer to 'get_entry' for full data, which is useful complementary guidance. However, it does not explicitly contrast this tool with other search tools like 'search_tracks' or the various list tools, so an agent may need to infer when this is the appropriate choice among siblings.

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?

The description explicitly states 'Metadata only: no audio file,' which is a key behavioral constraint that informs users what the tool will not return. It also specifies that only 'Published tracks' are included, and the query-mapping examples clarify how search terms are interpreted (e.g., 'dungeon' as keyword), giving insight into the tool's behavior beyond a simple list of parameters.

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 compact yet information-dense, combining a clear purpose, a behavioral note, and three illustrative query mappings in a few sentences. It avoids redundancy and stays focused on the most important aspects for a user, though the examples add a little length without detracting from clarity.

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?

Given that there is no output schema, the description partially addresses return format by mentioning that results include composer, album, moods, keywords, duration, and page URL. It does not describe pagination or sorting behavior of results, but the presence of limit/offset parameters implies them, and the core return fields are covered sufficiently for a search tool.

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 schema already provides descriptions for 10 of 13 parameters (77% coverage), which meets the high-coverage baseline. The description adds useful mapping examples for genre, type, and keyword but does not elaborate on sort, limit, or offset beyond their self-explanatory names; thus it offers moderate added value but not exhaustive parameter explanation.

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 searches published tracks of MGS Audio, listing the key attributes (composer, album, moods, keywords, duration, page URL) and explicitly notes it returns metadata only. It also provides concrete examples mapping natural-language queries to specific fields (genre, type, keyword), which removes ambiguity about the tool's scope.

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 description includes practical usage examples (e.g., 'a battle theme' → genre: 'Combat', type: 'music'), effectively teaching how to construct queries. While it does not explicitly contrast with sibling tools like search_encyclopedia, the focus on music tracks and metadata makes the intended use case clear, and the examples provide enough guidance for typical usage.

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