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

No annotations are provided, so the description carries the full burden. The verb 'Detect' strongly implies a read-only operation; however, it does not explicitly state that no modifications or side effects occur. The description gives sufficient functional context but stops short of stating non-destructive 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 concise, consisting of two sentences that deliver purpose and usage without fluff. The parenthetical examples add useful specificity without unnecessary elaboration.

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 tool's simplicity, the description covers the essential context: what it detects, when to use it, and why it matters (avoiding pipeline mismatches). It does not describe the return format, but that is not critical for a detection tool and the output schema exists separately.

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 only parameter, project_dir, is not elaborated in the description at all. While the name suggests a file path, there is no mention of expected format, whether it should point to a root folder or a specific file, or any related constraints. With 0% schema coverage, the description should compensate but does not.

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 purpose with a specific verb ('Detect') and resource ('engine, version and render pipeline of a game project'). It distinguishes itself from sibling tools by focusing on detection rather than mutation or retrieval.

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 instructs when to use the tool: 'Call this BEFORE recommending or importing assets.' This provides a direct usage trigger and sets expectations for preconditions, leaving no ambiguity about when it should be invoked.

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 behavioral burden. It conveys a read-only lookup and previews the output fields, but it does not disclose failure modes, authorization/ownership consequences, or any limitations. It is minimally adequate for a simple getter.

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 filler; every phrase contributes either scope ('one owned asset') or expected content. Exemplary concision for a simple lookup.

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 output schema covers return-value structure, so the description doesn't need to restate it, and the one-parameter tool is simple. However, the description omits when to use the tool versus its siblings and leaves parameter semantics underspecified, so it is adequate but not 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?

Schema description coverage is 0% and the lone asset_id parameter is never defined, formatted, or tied to the description beyond the phrase 'one owned asset.' The description does not compensate for the missing parameter documentation.

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 ('one owned asset') and enumerates the returned content ('summary, usage notes, gallery/video links, store URL'). It does not use an explicit verb beyond the tool name, and the contrast with siblings like search_owned_assets is only implicit, so it falls short of a 5.

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?

'One owned asset' implies this is for retrieving details on a specific already-known asset rather than searching across assets, but the description never explicitly says when to prefer it over search_owned_assets or other siblings. Usage context is implied, 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?

With no annotations available, the description carries the full burden and does disclose meaningful behavior: it performs a 3-way hybrid search (FTS + BGE + CLIP) and returns recommendations mapped to aspects of the problem. It does not explicitly mention side effects, permissions, or non-mutation, but 'recommend' strongly implies a read-only sweep.

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 dense, well-structured sentence. It front-loads the input and purpose, includes a useful example, and adds meaningful algorithmic detail without 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 covers the main input, the search approach, and the intent of the output, and the output schema can explain return values. However, it omits the semantics of limit_per_category and provides no guidance on how this tool compares to sibling search/recommendation tools.

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 gives clear semantics for problem_description, including a concrete example, but says nothing about limit_per_category. With schema description coverage at 0%, the optional parameter's meaning is left entirely to inference from its title and default value.

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 what the tool does: it sweeps the vault via hybrid search and recommends owned packages for a given game/feature description. It is distinct in behavior from siblings like search_owned_assets, though it does not explicitly name or contrast them.

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 usage context is implied: provide a game/feature description to get package recommendations. However, it does not state when to prefer this tool over search_owned_assets or other sibling tools, nor does it provide any exclusions or alternative conditions.

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 present, the description carries the behavioral disclosure burden. It discloses the nature of the output in useful detail: totals per engine, per category, and download status breakdown. Being a read-only stats endpoint, this is sufficient transparency, though it does not explicitly state that no mutation occurs.

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 filler. Every phrase adds concrete information about the aggregation dimensions and the local-versus-cloud distinction.

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 no-parameter aggregate stats tool with an output schema present, the description tells the agent exactly what dimensions the stats cover. Nothing crucial is missing for selecting or invoking this tool 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 tool has zero parameters, so parameter semantics are inherently non-issue. The baseline of 4 applies, and the description correctly implies that the tool operates over the entire vault without requiring 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?

The description clearly identifies a specific resource (vault) and the kind of output (overall stats), listing concrete aggregation dimensions: assets per engine, per category, and local vs cloud-only counts. It implies a broad overview role among the siblings, though it does not explicitly name an alternative to distinguish itself.

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 'Overall vault stats' signals that this tool is for high-level aggregate information rather than per-asset or per-category detail, so usage context is implied. However, there is no explicit statement of when to use this tool versus siblings like get_asset_details or list_asset_categories, and no exclusions are given.

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 behavioral burden and does disclose real traits: the local=true restriction, the required shape of project_dir, and the non-obvious side effect of installing a bundled UPM package as an embedded package in <project>/Packages/<name>/. It does not mention overwrite/reversibility or permissions, so it is not exhaustive.

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 sentences, front-loaded with the core action and constraint. The embedded-package sentence is dense but adds genuinely useful behavior rather than restating the schema, so little is wasted.

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?

An output schema exists, so return-value explanation is unnecessary, and the description still flags embedded_packages as a notable output signal. For a write tool with no annotations, it should ideally note overwrite behavior or failure modes, but the essentials for correct invocation are present.

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%, so the description must compensate, and it does: project_dir is explained as the project root (the folder containing Assets/), and asset_id is tied to the local=true tagging rule. The two parameters are semantically covered, though asset_id format is not specified.

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 gives a specific verb and resource: unpack a locally-downloaded .unitypackage directly into a Unity project's Assets/ folder. It implicitly separates this from the discovery siblings by noting that search comes first, so an agent can tell it apart from search_owned_assets and get_asset_details.

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 states an explicit precondition (only assets tagged local=true) and routes the agent to check with search first, which maps to the search sibling. It does not state when NOT to use it or what happens on a non-local asset beyond 'only works', leaving a small gap.

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 behavioral burden. The verb 'List' implies a read-only operation and the description states the output shape, but it does not disclose potential nuances such as whether categories with zero assets are included, ordering, or data freshness.

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 the action and resource, containing no redundant or filler 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?

With zero parameters and an output schema present, the description fully covers what an agent needs to invoke the tool correctly. There is no need to explain return values because the output schema already exists.

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 no semantic ambiguity to clarify. The baseline of 4 applies because there are no parameters at all.

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 ('List') and resource ('categories'), and clearly states the output: how many owned assets fall into each category. This distinguishes it from siblings like search_owned_assets or get_vault_stats, which target different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives, no mention of scenarios that favor a sibling, and no exclusions or prerequisites. An agent must infer usage solely from the name and the literal description.

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 the full behavioral burden. It discloses that the tool is personalized by resolving against the user's OWN library and explains the output shape: each recipe lists which owned assets fill each slot. This gives meaningful behavioral context beyond the tool name, though it does not explicitly state side-effect absence.

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 short sentences with no filler. It front-loads the core purpose and immediately clarifies the key distinguishing behavior and return format, making every sentence informative.

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 zero parameters, no annotations, and an existing output schema, the description is complete enough for an agent to invoke the tool correctly. It defines the resource, the personalization scope, and what each returned recipe contains, so no critical operational detail is missing.

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 the baseline is 4. The description adds value by indicating that the user context is implicit and that results are scoped to the user's own library, which is the relevant semantic context despite the empty parameter list.

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 ('list') and a clear resource ('curated production stacks' / 'asset recipes'), then clarifies the differentiating scope: they are resolved against the user's OWN library. This distinguishes it from siblings like get_stack_recommendations and search_owned_assets by emphasizing curated, owned-asset-specific recipes.

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 the tool: when the user wants curated recipes resolved against their own library rather than generic recommendations or raw asset search. However, it does not explicitly state when-not-to-use it or name any sibling alternative, so usage guidance is inferred 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 present, the description carries the full behavioral burden and delivers substantive traits: the 3-way RRF fusion of FTS5/BGE/CLIP, result 'match' attribution ('keyword+semantic+vision'), and the ownership distinction ('vault_owned' vs 'catalog_grant'). It also discloses engine-agnostic matching behavior for Quixel and Cosmos sources. It stops short of pagination, rate limits, and error behavior, but the core result-interpretation behaviors are well covered.

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 purpose line is front-loaded, followed by two compact behavioral notes, then a terse parameter block where each line earns its place with inline enums. No filler, no repetition of schema defaults. The structure is scannable and information-dense.

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 output schema covers return structure, so the description rightly focuses on filtering semantics and result interpretation. For a 7-parameter hybrid-search tool with zero annotations, it covers the essentials: marketplaces, engine-agnostic matching, render pipeline, and ownership/match attribution. Remaining gaps—query syntax, pagination beyond limit, and empty-result behavior—are modest 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 description coverage is 0%, so the description must compensate, and it does for 5 of 7 parameters: engine, source, pipeline, local_only, and limit all receive meaningful semantics with inline enum values (e.g., 'all|unity|fab|quixel|gumroad|cosmos'). The engine note adds genuine nuance ('Engine-agnostic sources... match both unity and unreal'). query and category remain unexplained, with query—the only required parameter—lacking any guidance on accepted query syntax.

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?

Opens with a specific verb and resource: 'Search the user's asset vault across Unity, Fab, Quixel Megascans, Gumroad, and Cosmos.' The enumerated marketplaces and the vault scope clearly distinguish it from siblings like get_asset_details, list_asset_categories, and get_vault_stats. The hybrid-search detail ('keyword (FTS5) fused with BGE text embeddings and CLIP visual vectors') reinforces that this is the vault search operation.

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 context is implied rather than explicit: the name and first line mark this as the vault search tool, and filters like local_only ('only assets already downloaded to disk') hint at concrete use cases. However, the description never states when to prefer this over siblings (e.g., get_asset_details for a known asset, list_asset_categories for taxonomy) or any exclusion conditions. An agent must infer the division of labor from sibling names alone.

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 behavioral burden. 'Lint' and 'detects' imply a non-mutating validation pass, and the specific detection categories explain what the tool does. It does not explicitly state side-effect freedom or permission requirements, but the language strongly signals read-only analysis for a pre-import check.

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 with no filler: purpose, concrete detection examples, and a single usage directive. The most important information is front-loaded, and every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single input parameter, no annotations, and an existing output schema, the description covers purpose, input semantics, and when to call it. It could explicitly confirm that no changes are made or name sibling alternatives, but it leaves no major workflow ambiguity for a validation 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 0% and the only parameter, asset_ids, has an empty items schema. The description compensates by clarifying that these are 'owned assets planned for one project/stack,' and the plural usage plus 'importing multiple assets' conveys that all intended assets should be passed together.

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 and resource: 'Lint a set of owned assets that are planned for one project/stack.' It also enumerates concrete outputs (role conflicts, family notes, missing prerequisites), which makes it clearly distinct from siblings like get_stack_recommendations or audit_project without requiring schema inspection.

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 invocation context: 'Call before importing multiple assets together.' It does not name alternative tools or exclusion conditions, but the workflow placement is clear enough for an agent to choose this over search, recommendation, or import tools.

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