Polyfork low-poly 3D assets

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

With no annotations provided, the description must carry the behavioral burden. It discloses the sorting hierarchy ('same kit first, then shared palette, then compatible real-world scale'), the diversification behavior ('spread across classes'), and the return format ('ready preview URL'). This is substantial, though it does not mention read-only status or error behavior, which would make it fully transparent.

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. It uses two sentences: one to explain the matching logic and criteria, and one to state the use case and return value. Every word adds value, with no redundancy or fluff.

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 query tool with a schema and no output schema, the description explains the core return value (assets + preview URL) and the matching behavior, which is sufficient for an agent to invoke it. It could elaborate on the structure of the returned asset list or error conditions, but the given context covers the essential information.

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 provides descriptions for free, limit, and max_triangles (60% coverage), while id and min_triangles lack descriptions. The description adds context about the matching criteria, which indirectly informs parameters like id (the 'one asset') and limit (diversity control), but it does not explicitly detail parameter meanings or provide examples. Given moderate schema coverage, a 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?

The description uses a specific verb ('return') and clearly identifies the resource ('assets that BELONG IN A SCENE WITH IT'). It distinguishes itself from siblings like get_asset and search_assets by focusing on scene compatibility rather than general search or retrieval, and explicitly states its purpose as 'turn a single pick into a scene'.

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 'Use this to turn a single pick into a scene' provides a clear, actionable use case, and the description implies when it is appropriate compared to searching for assets generally. However, it does not explicitly state when not to use it or name alternative tools, so it lacks the full exclusion guidance that would merit a 5.

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 provided, the description carries full burden. It details special cases (has_ik returning gait/arm blocks), paid-asset behavior (returns price and buy link), and caller-specific download URLs. It also instructs to 'quote both' for paid assets, providing rich behavioral insight.

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 front-loaded with the primary purpose and each subsequent sentence adds valuable specifics. It is somewhat dense, especially the first sentence, but there is no redundancy or filler, making it appropriately concise for the information conveyed.

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 no output schema, the description thoroughly explains all return scenarios: standard asset details, the has_ik block, and paid-asset fallback. It also mentions how the data can be applied, making it complete for a one-parameter 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 documents the only parameter 'id' with a clear example. The description adds no additional meaning about the parameter itself, only about the output. With 100% schema coverage, 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?

The description clearly states 'Full detail for one asset' and enumerates specific returned fields (size, triangle count, palette, animatable parts, renders, download URLs). This distinctly differentiates it from sibling search/list tools by focusing on retrieving comprehensive data for a single asset.

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 conveys clear usage context: when you need full detail for a specific asset and even how the data can be used (e.g., with /cdn/walk.mjs). However, it does not explicitly mention alternative tools or when not to use this one, so it lacks explicit exclusions.

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 discloses the types of content and even names specific rules (real-world metres, one material, never rescale to fake a fit), giving useful behavioral context beyond what structured fields show.

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 purpose and filled with concrete examples. Every clause earns its place, and the length is appropriate for the instructional content.

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 help tool with a single optional parameter, the description fully covers what the tool returns and when to use it. The enum topics are self-explanatory, and no output schema is needed for help content.

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% with an enum for topic and a description 'omit for the overview'. The tool description itself does not add parameter details, but schema already documents the single optional parameter. Baseline 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?

The description clearly states this is a help tool for using the server, with specific content: metadata meaning, easy-to-get-wrong rules, and worked recipes. It distinguishes itself from sibling lookup tools by being a meta-tool that explains server usage.

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?

Explicitly says 'Call it when a tool did not behave as you expected, or before a multi-step build, instead of guessing.' This provides clear when-to-use guidance and states the alternative (guessing) to avoid.

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 safety and behavior burden and does well: it discloses that filling-up kits are not sold as bundles, that parts returned are those existing today, and that free parts need no account while others require Pro. It does not describe output format or errors, so not 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?

Three focused sentences, with the main action in the first line and supporting context in the next two. Every sentence contributes new information: the return value, the filling-up behavior, and the recommendation/account guidance.

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 read-like list tool with no output schema, it reasonably covers purpose, usage context, Pro/account constraints, and the compact flag implication. It omits exact response fields and error handling, but the cross-reference to get_asset supplies return-detail semantics. Overall sufficient for an agent to invoke 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 description covers 100% of parameters (id and compact), so baseline is 3. The description adds context about full detail vs. composing a scene, but does not add syntax, formats, or behavior beyond what the schema already explains for either parameter.

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 opens with a specific verb+resource: returns every published part of one kit, and distinguishes itself by referencing get_asset's detail level. It also clarifies the kit-composition use case, making it clearly different from listing kits or fetching a single asset.

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 gives concrete context: works on filling-up kits and returns currently available parts. It even advises recommending parts rather than the kit in that state, including account/Pro implications. It does not explicitly enumerate when to prefer get_asset over get_kit, but the reference to get_asset implies the boundary.

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 fully carries the behavioral burden. It discloses that terrain is non-flat (y=0 is wrong), returns ground height and slope for `at`, flat building sites, profile details (heights, grade, underwater points), world-coordinate alignment, and how kits join on a 64m grid. This is rich, transparent 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?

The description is somewhat longer than necessary but front-loaded with the core question. Every sentence adds value (e.g., explaining world coordinates, grid joining), so it is not wasteful. Minor redundancy could be trimmed, but structure is effective.

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 complex 8-parameter tool with no output schema, the description covers the essential workflow: height lookup, flat areas, profile querying, and coordinate system. It doesn't detail every parameter, but the schema already does. It also adds context for multi-kit terrain joining, making it quite complete for its complexity.

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 baseline is 3. The description adds meaningful context for key parameters: it explains how `at` returns a height to set as position.y, and how `profile` returns grade and underwater status. It also clarifies the output concept of 'flat_areas' (though the schema parameter is `flats`), slightly enhancing the schema's field descriptions.

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 explicitly states the tool's purpose: to determine the correct ground height for placement ('AT WHAT HEIGHT DO I PLACE THIS') and to identify buildable areas ('and where can I build'). It clearly differentiates from sibling tools like `get_asset` or `list_kits` by focusing on terrain-specific procedural generation and placement support.

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 clear usage guidance: use it before laying out a town, farm, or depot, and use `profile` for roads/walls. It does not explicitly name alternative tools or exclusions, but the context strongly implies this is the dedicated tool for terrain queries.

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 and discloses key behaviors: matching logic (against knob names/option values, not colours), output components (createAsset call plus GLB URL), and confidence handling (tell the user when confidence is below high). This is valuable beyond the 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?

The description is two sentences, each serving a distinct purpose: explaining the transformation process and providing confidence-handling guidance. It is dense but not bloated; the examples in the first sentence are helpful but slightly redundant.

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 tool with no output schema, the description covers the essential output (ready createAsset call, GLB URL) and handles the main complexity (confidence). It does not fully describe the response structure or compare with siblings, but it is largely complete for a moderately complex parameter set with a rich schema for 'look'.

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 67% (want and look have descriptions, id does not). The description adds significant meaning to 'want' by explaining how matching works and what vocabulary to use. The look parameter is already fully described in the schema, so the description's contribution is primarily for 'want'.

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 action: turn a plain-words request into a ready createAsset() call with a GLB URL for a variant. It implicitly distinguishes from siblings like get_asset by focusing on variant generation, though it does not explicitly name alternatives.

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 gives clear guidance on how to use the want parameter—matching against knob names and option values from -params.json, not colour vocabulary—and instructs checking confidence and communicating inaccuracies. This is strong contextual usage guidance, though it does not mention when to choose this tool over 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?

With no annotations, the description carries the transparency burden. It adds useful context about kit statuses ('published' vs 'filling-up') and clarifies that filling-up kit parts are usable today, which helps the agent interpret results. However, it does not disclose the return format, pagination, read-only nature, or any other tool-specific 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?

The description has four sentences, each contributing domain definition, usage guidance, status explanation, or an alternative tool. It is slightly longer than the minimal 'list kits' statement, but every sentence earns its place without being verbose.

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 list tool with no output schema, the description covers the key context: what kits are, when to use them, their statuses, and how to fetch parts. It does not explicitly state that the tool returns a list of kits with their statuses, but the name and context make that sufficiently clear.

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 has zero parameters, so schema coverage is effectively 100%. No parameter description is needed, and the baseline of 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 clearly identifies kits as the resource and distinguishes this tool from get_kit, which fetches parts. However, it never explicitly states that list_kits lists all kits; the purpose is inferred from the tool name and the usage guidance rather than stated directly.

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 explicitly says when to reach for a kit ('building a whole environment rather than looking for one object') and points to an alternative ('Use get_kit to fetch the parts of either'). This gives clear context for when to invoke this tool versus related 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?

With no annotations, the description carries the burden of behavioral disclosure. It explains that the tool returns a URL, works with paid assets via a public preview, and includes pricing/purchase info. While it could have been more explicit about read-only nature or error handling, it covers the key behavioral nuance well.

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 three concise sentences, each earning its place: purpose, usage alternative, and paid-asset behavior. It is front-loaded with the most important information and contains no fluff.

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 one-parameter tool with no annotations or output schema, this description is highly complete. It covers what the tool does, when to use it, how it handles paid assets, and what the result contains, leaving little ambiguity.

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 fully describes the 'ids' parameter (array, up to 24, any order). The description adds only minimal context by mentioning 'assets' and 'scene' composition, but does not go beyond schema. Baseline of 3 is appropriate given 100% 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 composes assets into a scene and returns a URL the user can open and orbit. It distinguishes itself from sibling tools by focusing on scene composition rather than individual asset retrieval, and explicitly contrasts with handing over three.js code.

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 explicit guidance to use this tool instead of providing a three.js block the user cannot run. It also provides context on handling paid assets, instructing to pass on pricing information to avoid 404 surprises.

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 explains this is a reporting/feedback call ('a report costs one call and is how this server gets better') and clarifies the four kinds. It does not detail post-call side effects such as whether a record is persisted, but the core behavior is disclosed.

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, well-structured paragraph that is front-loaded with the core purpose. It uses space efficiently to explain the four kinds and a motivational nudge, with no tangential details.

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 reporting tool with a rich schema and no output schema, the description provides enough context: what it does, how to use it, and the meaning of kinds. It does not state the return format, but that is not critical for a fire-and-forget report call; the overall guidance is complete enough.

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 covers all 5 params, so baseline is 3. The description adds substantial meaning to the `kind` enum by explaining each value in context, and provides an example for `need` ('we do not have that'). This raises it above baseline.

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 opens with a clear verb+resource ('Report a gap'), then enumerates four distinct kinds and explicitly contrasts server-side vs catalogue gaps, making it unambiguous and well-differentiated from sibling tools like search/get.

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 gives explicit usage guidance: 'offer this whenever a search is empty or thin' for asset kind, and defines scenarios for capability, output, and docs. It also encourages use rather than silence, providing clear context for when this tool is the right choice.

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 important behavioral traits: results mix FREE and PRO assets, paid assets come only with a plan, and it tells the agent to quote the plan and clarify which is which. It also explains how to handle poor coverage. However, it omits any mention of read-only nature, rate limits, or error behavior, so it is not 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?

The description is a single paragraph of about 110 words, front-loaded with the core purpose. Every sentence adds value, though the later part about quoting plans and handling poor coverage is slightly verbose. Still, it remains efficient and well-structured.

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 11 parameters and no output schema, the description covers key behavioral context: result composition, pricing model, and fallback behavior. It mentions coverage and the free/plan fields, giving the agent a sense of the result shape. It does not list all parameter behaviors, but the schema handles those. Overall, it is fairly complete 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?

Schema coverage is 73%, so the description need not fully compensate. The description adds guidance for triangle budget usage and mentions output fields (free, plan), but does not elaborate on parameters like sort, class, or min_triangles. This is adequate given the schema's own descriptions, but not exceptional.

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 opens with a specific verb+resource: 'Search the Polyfork catalogue of low-poly 3D assets for three.js.' This clearly distinguishes it from sibling tools like get_asset (which retrieves a single asset) and list_kits (which lists kits). The purpose is unambiguous.

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 explicit when-to-use guidance: 'Use this whenever the user needs a model for a scene, game or site.' It also gives context for filtering by triangle budget and instructs to offer report_need instead of substituting unrelated assets when coverage is poor, which serves as a when-not and an alternative.

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 of disclosing behavior. It explains what information is returned (key status, owned assets/kits, download viability) and implies a read-only diagnostic nature. However, it does not explicitly confirm non-destructiveness or describe the response format.

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 the first sentence front-loading the tool's purpose and the second providing usage guidance. Every word contributes, and there is no redundancy or fluff.

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, the description gives sufficient context: what the tool reveals and when to call it. It is almost complete, though it omits the exact return format, which is a minor gap for agents expecting structured output.

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, so there is nothing for the description to explain. The baseline of 4 applies, and the description adds no unnecessary parameter details.

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 indicates the tool reports the connection's current state: key attachment, owned assets/kits, and download viability. It distinguishes from siblings by focusing on the connection rather than individual assets or kits, though it lacks an explicit verb like 'retrieve' or 'list'.

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 explicitly states when to call the tool: 'before promising the user a paid file' and 'when a download 404s'. It provides concrete usage scenarios but does not mention when not to use it or compare to alternative tools.

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