Swarme

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

No annotations are provided, so the description carries the full disclosure burden. It clearly indicates a read operation that returns data and scopes it to the authenticated machine client, implying an authentication precondition. It does not mention error cases, rate limits, or whether the call itself affects metered usage, but for a simple balance read the core behavior is transparent enough.

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 clause adds information: the resource, the data categories returned, and the scope of the data. It is appropriately sized for a parameterless read tool.

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

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

With zero parameters and an output schema present, the description covers the essential invocation context: the resource, the data categories, and the authentication scope. Nothing an agent needs to issue this call correctly 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 is empty, so parameter semantics are trivially satisfied. The description adds value by clarifying what the returned data covers – credit, metered usage, and spend-limit status – beyond what the empty schema can convey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Return') and a clear resource ('Swarme account balance'), and enumerates exactly what is included (credit, metered usage, spend-limit status). This distinguishes it from sibling status tools like swarme_ai_status and swarme_tool_status, which focus on service or tool status rather than account balance.

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 the tool's use case – reading the authenticated client's balance – but gives no explicit guidance about when to prefer it over sibling read/status tools, nor any exclusions. The 'authenticated Swarme machine client' phrase provides some scope context, placing this at the implied-usage level rather than no guidance at all.

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 of behavioral disclosure. 'List' implies a read operation and 'metered' hints at cost implications, but the description doesn't state whether listing incurs charges, requires authentication, or has any default ordering or filtering 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 a single front-loaded sentence with no filler. It is efficiently sized, though phrases like 'metered human and machine workflows' are somewhat vague and could be more 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?

The operation is simple and an output schema exists, so return structure doesn't need explanation. However, the description is missing when to use the tool, what the sort values mean, and default behavior, leaving clear gaps for an agent choosing or invoking this 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%, and the description says nothing about the `sort` or `limit` parameters. The enum values ('all', 'hot', 'new') and min/max are self-descriptive at a basic level, but 'hot' is ambiguous and no parameter-level meaning is added in the description.

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 ('curated AI models'), and it adds context by noting they're available for 'metered human and machine workflows.' This distinguishes it from sibling run/status/capability tools at a glance, though it does not explicitly name an alternative.

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 use this tool versus alternatives like swarme_ai_run, swarme_ai_status, or swarme_capabilities_search. It is easy to infer this is the model catalog, but the description never states that inference or mentions any 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?

With no annotations, the description carries the full burden. It usefully discloses two behaviors: the operation is queued ('Enqueue') rather than synchronous, and it consumes the authenticated account credit balance. However, it omits details like what happens with insufficient credits, whether the operation is reversible, and what the queued job returns beyond what the output schema might provide.

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. It communicates the primary action and a key cost constraint efficiently, though it sacrifices useful detail for brevity.

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 three undocumented parameters and an output schema, the description is too thin. It does not explain how to identify a valid slug, what prompt constraints matter beyond the schema's maxLength, or what options accepts. The lack of usage guidance also leaves the agent uncertain about when this tool is the right choice among many siblings.

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 explain slug, prompt, or options at all. An agent must guess what 'curated AI model' implies for the slug parameter and what options might contain. The description adds no semantic value for any of the three parameters.

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 identifies a specific action ('Enqueue') and resource ('curated AI model'), and adds the meaningful constraint of using the account credit balance. It does not explicitly differentiate from sibling tools like swarme_tool_run, and 'curated' is somewhat vague, but the core purpose is clear.

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 provided about when to use this tool versus alternatives such as swarme_tool_run, swarme_experiment_create, or swarme_ai_models. The description implies a use case but states no conditions, exclusions, or prerequisites beyond having a credit balance.

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

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

No annotations are provided, so the description carries the full burden. It does convey that the operation returns status and sanitized output, which implies a read-only, non-destructive behavior and discloses that output is sanitized. However, it does not mention error behavior, whether the job runs asynchronously, or what 'sanitized' means in practice.

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 word adds meaning, and the key action and object are presented immediately.

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 operation is simple with only one parameter and an output schema, but the absence of annotations and usage guidance leaves the agent to infer when to call this instead of related status tools. The description is minimally viable but not fully complete for correct tool selection in a large sibling set.

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 explain job_id beyond the tool name. While job_id is fairly self-explanatory, the description fails to specify where the ID comes from, its expected format, or any constraints beyond the schema's 'required' flag.

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 a specific action ('Return status and sanitized output') on a specific resource ('one AI model job'). It aligns with the tool name and title, and the phrase 'AI model job' distinguishes it from sibling status tools like swarme_tool_status and swarme_experiment_status, though not explicitly.

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

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

The description gives no guidance on when to use this tool versus alternatives, how to obtain a job_id, or whether to poll it after swarme_ai_run. With many sibling run/status tools, this lack of usage direction is a clear 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?

With no annotations provided, the description carries the full burden but reveals only the basic operation. It does not disclose behavior such as default limits, result ordering, partial matching behavior, or whether empty queries are allowed. The description adds minimal context beyond a restatement of the name.

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, well-formed sentence that communicates the core purpose immediately with no filler or redundant phrasing. It earns its place and is structured effectively.

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 a relatively simple search with an output schema and no required parameters, so minimal context suffices for basic invocation. However, the description does not clarify how this search differs from nearby sibling tools or what kinds of categories are valid, leaving some practical ambiguity for an agent deciding whether to call it.

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 needs to compensate. It explicitly maps 'query' to 'keyword' and 'category' to 'category', adding slight semantic value, but it does not explain the 'limit' parameter or how the parameters interact. Parameter names are self-descriptive, but the description doesn't fully fill the coverage gap.

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 a specific verb ('Search'), a resource ('Swarme tool capability registry'), and the two main dimensions ('keyword and category'). It does not explicitly contrast with sibling search tools like swarme_discover_search, but the target registry is unambiguously identified.

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 use this tool versus similar siblings such as swarme_discover_search or swarme_capability_describe. The description implies a general search use case but provides no context, exclusions, or selection criteria.

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. 'Return' implies a read-only lookup, and the tool appears simple and non-mutating. However, it does not disclose error behavior, authentication needs, rate limits, or what happens for an invalid slug.

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 sentence with no filler. It is front-loaded with the verb and resource, making it easy to scan.

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 and has an output schema, so return-shape documentation is not necessary. However, the description lacks any pointer to how a valid slug is discovered, such as consulting the sibling capabilities_search tool, which an agent would need for correct invocation.

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 for the undocumented 'slug' parameter. It does not explain what a slug is, how to obtain a valid one, or how the slug maps to a capability. The only clue is the tool name and the phrase 'one Swarme capability'.

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'), the resource ('one Swarme capability'), and the result ('the schema'). It is easy to distinguish from the sibling search tool, though it does not explicitly name an alternative.

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 provided about when to use this tool versus capabilities_search or other siblings. The intended use is only implied by the phrase 'one Swarme capability', not explicitly 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, the description carries the behavioral burden. It clearly signals a read-only action and restricts access to public or unlisted owner-verified passports, which is meaningful access context. It does not discuss auth or not-found behavior, but for a simple read-by-ID operation the core behavior is unambiguous.

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 with no filler. It front-loads the action ('Read'), states the resource, the access scope, and the lookup key. Every word earns its place.

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

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

For a one-parameter read tool with an output schema present, the description covers the resource, the access scope, and the identifier. It omits alternative routing and error semantics, but those are less critical here; the core call contract is fully usable.

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 supply parameter meaning. It does so by identifying the key as a UUID, which maps directly to the sole required passport_id parameter. The schema's regex pattern already encodes format, but the description adds the conceptual role.

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?

Description uses a specific verb ('Read') and resource ('Passport'), and scopes the operation to 'one public or unlisted owner-verified Passport by UUID.' This clearly distinguishes it from sibling discover_search: read requires a known UUID, search is for discovery.

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

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

The phrase 'by UUID' implies this tool is appropriate when the caller already has a passport identifier, while search tools would be used to find one. However, no alternative tool is named, and there are no explicit when-to-use or when-not-to-use instructions, leaving the guidance 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?

With no annotations, the description carries the full burden. It discloses meaningful filtering behavior beyond the tool name: only public, active, owner-verified passports are returned, and unlisted/private ones are excluded. This is genuinely useful behavioral context for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two crisp sentences with zero filler. The core scope and exclusions are front-loaded, and every sentence contributes meaningful 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?

Despite having an output schema, the description is incomplete for a 5-parameter search API with no annotations and no schema-level parameter descriptions. An agent cannot reliably know how to construct queries, whether host is a filter, or what page and limit control beyond their obvious names. The description covers scope but not request semantics.

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 adds nothing about the five parameters (query, host, page, type, limit). It does not explain how filtering works, what query searches against, how pagination behaves, or how type interacts with the search. The description completely fails to compensate for the lack of schema-level 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 uses a specific verb ('Search') and a precise resource ('public, active, owner-verified Swarme Passports'). It also defines the excluded scope ('Unlisted and private records are excluded'), making the tool's purpose immediately clear and distinguishing it from siblings like swarme_discover_read.

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 clearly frames when this tool is appropriate: searching public, active, owner-verified passports. It also gives a concrete exclusion by stating that unlisted and private records are not included. However, it does not explicitly point to an alternative such as swarme_discover_read for those excluded records.

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 must carry the full behavioral burden, but it only states that models are run against a brief with a credit budget. It does not disclose whether execution is asynchronous, whether credit is consumed immediately or only on completion, what 'compatible' means, or what side effects occur.

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 words; it earns its place. It is concise to the point of under-specification, but that is better penalized under other dimensions rather than structure.

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 6-parameter tool with nested objects, two enums, and no annotations, the description is far from complete. It fails to clarify model compatibility, objective semantics, blind mode, or budget behavior; although an output schema exists, the input side remains inadequately described.

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, but it only loosely maps to 'models' (2–6 models) and 'budget_units' (credit budget). It does not explain the 'task' enum, the 'input' object structure, 'blind', or 'objective', leaving most of the 6 parameters semantically underdefined.

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 and resource: 'Run 2–6 compatible models against one canonical brief with a credit budget.' This clearly conveys the tool's multi-model experiment purpose and differentiates it from single-run sibling tools like swarme_ai_run or swarme_tool_run.

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 the tool is for running multi-model experiments with a budget, but it does not explicitly say when to prefer this tool over alternatives or mention exclusions such as single-model runs or non-experiment workflows. The usage context is present but left largely 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?

With no annotations, the description carries the full burden of disclosing behavior. It does reveal that the tool selects and records (a write-like action), but it does not explain whether the winner selection is permanent, whether it overwrites an existing selection, or what side effects occur on the experiment.

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 tight sentence with no filler, front-loading the primary action before the scoring detail. It is well-structured for quick parsing, even if some semantic information is missing.

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 mutation tool with no annotations and 0% schema description coverage, key information is missing: parameter semantics, when to invoke it relative to experiment lifecycle, and what the selection implies for the experiment. The presence of an output schema does not compensate for these gaps.

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 for the undocumented parameters. It only loosely hints at 'score' via 'bounded score' and at 'item_id' via 'experiment result', but it never explains what experiment_id or item_id actually refer to or how they relate.

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 ('Select') and resource ('completed experiment result') and adds the action of recording a bounded score, so an agent can tell this is the winner-declaring tool among experiment siblings. It does not explicitly name a sibling to differentiate from, so it stops 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?

The phrase 'completed experiment result' implies the tool should be used after an experiment has finished, which is some usage context. However, it does not say when not to use it or mention alternatives like swarme_experiment_status or swarme_experiment_create.

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 outputs are sanitized and that latency, credit use, scores, and state are returned, and 'Return' signals a read-oriented operation. It does not explicitly state side effects, auth requirements, or error behavior, but for a status query the disclosed behavior is reasonably complete.

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?

One short sentence lists the return payload in a scannable sequence without filler or repetition. It front-loads the verb and the key output categories and earns each word.

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 obvious parameter and an existing output schema, the description covers the main purpose and the kind of data returned. It omits explicit usage/alternative context and parameter provenance, but these are minor for a simple read-status 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 input schema has one required experiment_id with no description (0% coverage), and the tool description does not explain where the ID comes from or its format. Although the name is fairly self-explanatory, the description adds no parameter-level meaning, so it does not compensate for the missing schema 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 uses a specific verb ('Return') and names the resource ('AI Workbench Experiment') plus the exact data returned (sanitized model outputs, latency, credit use, scores, experiment state). This clearly identifies the tool as a status/result reader and differentiates it from sibling status tools like swarme_tool_status by focusing on experiment-specific artifacts and metrics.

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

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

Usage is implied: an agent needing current experiment results or status would pick this. However, the description gives no explicit condition for when to use it, no exclusions, and no pointer to alternatives such as swarme_experiment_create or swarme_experiment_select_winner, so the agent must infer selection from the tool name and output categories.

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. 'Return' implies a read-only operation and the absence of side effects, but it does not disclose behavior around invalid run IDs, empty results, or run-state requirements. It is adequate but minimal.

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 with no filler, front-loading the action and resource. It is appropriately sized for the tool's simplicity.

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 exists, so return values are covered, and the tool has only one required parameter. However, the lack of usage guidance and run_id semantics leaves the description slightly incomplete for an agent deciding when and how to call it.

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 only says 'for a Swarme capability run,' which loosely ties run_id to a run but does not explain what run_id is, where to obtain it, or any expected format. The description fails to compensate for the undocumented 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 ('Return') and resource ('artifact manifest metadata for a Swarme capability run'), and the title 'List Swarme Tool Artifacts' reinforces the action. This clearly distinguishes it from siblings focused on running, status, or cancellation.

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 no guidance on when to use this tool versus alternatives, such as after a swarme_tool_run completes or to inspect run outputs. No explicit context, prerequisites, or exclusions are provided.

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 disclosure burden and earns credit for disclosing that queued runs are cancelled while running runs are only sent a cooperative cancellation request. It does not cover error cases or side effects, but the core non-guaranteed behavior is 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 entire description is one front-loaded sentence with no filler, repeated claims, or redundant restatements of the title. Every clause adds either the resource or the cancellation behavior.

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

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

For a two-parameter cancellation tool, the description covers the key queued-versus-running behavior and the output schema exists, but it leaves parameter semantics and usage context unaddressed. It is adequate but not complete without annotations.

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 names neither run_id nor reason. An agent cannot learn from the description what reason means for cancellation or how run_id should be obtained/used, so the prose adds no parameter-level meaning.

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 the specific verb 'Cancel' and names the exact resource: a queued run or a running worker-backed Swarme capability run. It adds state detail that distinguishes cancellation from the status/run siblings.

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 makes clear that both queued and running runs are valid targets and that running runs receive only a cooperative cancellation request. It does not name alternatives, exclusions, or conditions for preferring another tool, so the usage guidance is implied 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It tells the agent this is a preparatory quoting step, but doesn't disclose side effects, whether the quote reserves prices/access, authentication requirements, or whether the tool is read-only.

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 focused sentence with no filler, and the key scoping phrase ('before running') is front-loaded. It could be improved by adding parameter or usage detail, but as far as brevity it is appropriately concise.

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 annotations and zero schema description coverage, one sentence is not enough. The agent is left without guidance on what slug to provide, what the input object should contain, and what happens after the quote is prepared. The existence of an output schema partially covers return values, but the invocation requirements remain under-specified.

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 doesn't explain either 'slug' or 'input'. 'Before running a Swarme capability' only loosely implies that slug identifies a capability; the nested input object is completely unaddressed. The description does too little to compensate for the empty schema docs.

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 clear verb ('Prepare'), a specific resource ('a price/access quote'), and its relationship to running a Swarme capability. It is distinguishable from sibling swarme_tool_run by the explicit 'before running' qualifier, though it doesn't name the sibling 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 phrase 'before running a Swarme capability' gives a clear temporal context for when to use this tool. It doesn't explicitly state when not to use it or name alternative tools, but the contrast with the run flow is evident from the wording.

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 does disclose one important trait: browser-first tools return a client execution plan rather than a direct result. However, it does not describe side effects, execution mode selection, authentication needs, or what happens for non-browser tools.

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 short, front-loaded, and contains no filler. Both sentences earn their place, though the brevity leaves material gaps in parameter and usage documentation.

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?

Despite an output schema existing, the tool has no annotations, no parameter descriptions, and minimal behavioral context. For a generic runner with nested input objects and a required slug, this description is not sufficient for an agent to invoke it reliably.

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 explain slug, input, or quote_id. An agent cannot infer what a 'slug' refers to, what shape 'input' should take, or when quote_id is required.

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?

Identifies a specific verb-resource pair ('Run or plan a Swarme capability') and adds the meaningful distinction that browser-first tools return a client execution plan. It is clearer than a tautology, though the dual 'run or plan' phrasing is slightly ambiguous about how the mode is selected.

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 is given for when to use this tool versus the many sibling tools such as swarme_tool_quote, swarme_capability_describe, or swarme_tool_status. The browser-first sentence hints at a behavioral condition, but it does not say when to choose run/plan versus alternatives or when not to use this tool.

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 must signal the side-effect profile. The verb 'Return' implies a read-only status query, but the description does not explicitly state that no modification or cancellation occurs, nor does it mention any auth or rate-limit behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no filler. It front-loads the return payload and keeps the resource scope clear.

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?

Since an output schema exists, the return values do not need detailed explanation. However, the description omits usage guidance and any detail about the run_id source, so it is minimally adequate rather than fully self-contained for an agent unfamiliar with the tool family.

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, run_id, has no schema description, and schema description coverage is 0%. The description adds some value by connecting run_id to a Swarme capability run, but it does not explain where run_id comes from, its format, or how to obtain it.

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 names a clear resource: status, cost, quote, and output metadata for a Swarme capability run. It is mostly distinguishable from sibling status tools, though it does not explicitly contrast itself with swarme_ai_status or swarme_experiment_status.

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 no guidance on when to use this tool versus alternatives such as swarme_tool_quote or swarme_ai_status, nor any prerequisites like calling swarme_tool_run first. The intended use is only implied by the run_id parameter and the term 'status'.

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 of behavioral disclosure. It reveals that the operation creates a signed reservation, but does not explain side effects, authentication requirements, expiration, or what the returned reservation is meant for.

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 sentence with no filler, which is structurally efficient. However, it is under-specified rather than genuinely concise—the vague jargon does not earn its place as the sole explanatory 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 5-parameter creation tool with no annotations and no schema descriptions, the description is far too thin. Even though an output schema exists, the agent still lacks understanding of what inputs mean, when to call it, and what behavioral expectations apply.

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 by explaining parameters. It does not mention slug, filename, mime_type, byte_size, or run_id at all, leaving all five parameters semantically opaque.

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 ('Create') and resource ('signed upload reservation'), which clearly distinguishes this from a generic upload tool. However, the phrase 'machine-native file capability' is vague and does not explicitly differentiate from sibling tools.

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 provided on when to use this tool versus alternatives, nor when not to use it. The phrase 'for a machine-native file capability' weakly implies a use case, but it is not actionable and does not name any sibling or exclusion.

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 burden, and it does disclose a significant behavioral trait: results are sanitized and omit content, bytes, tokens, and links. It does not mention pagination, ordering, or side effects, but the core read-only-looking behavior is communicated.

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 leads with the primary action and then specifies the key exclusions. Every phrase adds information, and there is no filler or repetition of the tool name.

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 presence of an output schema covers return-value structure, and the description explains the sanitization boundary. However, it lacks guidance on parameter semantics and does not clarify how the listing behaves with respect to the sibling tools, leaving an agent to infer usage context.

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 0% description coverage, and the main description does not mention 'limit' or 'include_templates'. The parameter names and types are moderately self-explanatory, but the description does not compensate for the schema's lack of explanations, nor does it explain how these parameters affect the returned inventory.

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 and resource: 'Return sanitized Vault document inventory metadata'. It clearly defines what the tool does and, crucially, what it deliberately excludes (contents, artifact bytes, share tokens, download links), which helps distinguish it from sibling tools like swarme_vault_fill and swarme_tool_artifacts.

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 this is a metadata-only listing operation, and the exclusions hint that it is not for retrieving content or artifacts. However, it does not explicitly state when to use this tool versus alternatives or provide any conditions that should route an agent to another sibling.

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 transparency burden. It does disclose two behavioral facts beyond the operation: the need for an owner-issued temporary grant and that responses contain only masked metadata. It does not explain overwrite semantics, idempotency, side effects, or why only masked metadata is returned.

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, tightly worded sentence that front-loads the operation, states the precondition, and adds the response characteristic. There is no filler or repetition of schema 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 an 8-parameter write operation with no annotations, the description is too thin to be fully actionable. It omits guidance on optional parameters, the meaning of field_id versus field_key, and how this tool relates to swarme_vault_fill. The output schema may describe return values, but the missing usage and parameter context remains 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?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only clarifies vault_grant as an 'owner-issued temporary grant.' The other seven parameters—field_label, field_value, field_id, field_key, value_type, field_group, and sensitivity—receive no semantic explanation beyond their schema names.

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 ('Create or update') and resource ('one Vault field'), and adds the key precondition of an 'owner-issued temporary grant.' This clearly distinguishes it from related tools like swarme_vault_fill, which imply bulk operations, and from read-oriented Vault tools.

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 a single Vault field needs to be created or updated and the caller has a temporary grant. However, it does not explicitly state when not to use it or name alternatives such as swarme_vault_fill for multi-field scenarios.

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 burden and does add behavioral details: a temporary grant is required, and the output is limited to sanitized document, billing, and one-use artifact-delivery metadata. However, it does not disclose side effects, persistence, or what 'bounded' means operationally.

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 wasted words. The primary action is front-loaded, followed by the key requirement and output limitation. Everything present 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?

Although an output schema exists and covers return values, the tool has 6 parameters, 0% schema coverage, and no annotations. The description fails to explain most parameters, lacks routing guidance versus siblings, and leaves important context (e.g., what 'bounded' means, how to obtain the grant, idempotency behavior) unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it only hints at two parameters: vault_grant ('owner-issued temporary grant') and template_body ('bounded template'). The remaining parameters (quote_id, output_format, template_title, idempotency_key) receive no explanation, leaving a significant gap for invocation.

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 ('Fill a bounded template using Vault data') and names the resource. However, it does not explicitly differentiate this tool from closely named siblings like swarme_vault_fill_quote, so it stops 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?

The description provides a prerequisite (owner-issued temporary grant) and a restriction on the return payload, which gives useful context. But it never says when to choose this tool over alternatives like swarme_vault_fill_quote or swarme_vault_documents, leaving usage largely implied.

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, but it only lists output metadata and says the quote is 'bounded.' It does not disclose whether quote-lock policy reserves or locks funds, whether the quote expires, or whether this operation is strictly read-only, which is significant for a quote/fill tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler or repetition. Every phrase contributes either to scope ('bounded Vault document-fill quote') or to the expected output contents ('wallet, spend, provider-cost, quote-lock policy metadata').

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?

Although an output schema exists and reduces the need to describe return values, the definition still lacks input semantics, usage context, and behavior around quote locking. The two parameters are not meaningfully explained, and there is no guidance on interacting with sibling fill/quote 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?

Schema description coverage is 0%, so the description must compensate, but it does not explain template_body or output_format at all. The phrase 'document-fill quote' weakly hints at template_body's role, but no actual parameter mapping or usage detail is provided.

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 names a concrete resource ('bounded Vault document-fill quote') with the key metadata fields it exposes. It does not explicitly contrast with siblings like swarme_vault_fill or swarme_tool_quote, but the 'quote' framing makes the pre-execution intent reasonably clear.

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 choose this tool over alternatives such as swarme_vault_fill or swarme_tool_quote. The name and 'quote' wording imply it is for obtaining an estimate before a fill, but the description never states this explicitly.

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 supplied, the description carries the full burden and does a solid job: it establishes an authenticated context, characterizes the result as masked/grouped metadata, and makes a strong guarantee that decrypted values are never returned. It does not discuss rate limits or pagination, but for a read-only summary the key behavioral traits are 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?

Two short sentences front-load the primary purpose and add only one high-value constraint. Every word contributes; there is no redundant restatement of the title or schema.

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 lightweight optional-parameter summary tool with an output schema, the description covers the core return behavior and safety guarantee. It is less complete on parameter semantics and sibling differentiation, so an agent may still need to infer the meaning of limit and include_fields before invoking.

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?

Input schema description coverage is 0%, yet the description never mentions what limit or include_fields control. The names and constraints (integer 1-200, boolean default true) provide some self-evident meaning, and include_fields can be loosely tied to 'masked field previews,' but the agent is left to guess the precise effect of each 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 names a specific verb and resource: 'Return profile metadata, grouped field counts, and masked field previews for the authenticated Vault.' The 'summary' focus and 'masked' language distinguish it from sibling Vault tools like vault_documents and vault_field_write even without naming 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 intended use is implied by the stated outputs, and 'Decrypted values are never returned' gives a clear negative signal for anyone needing raw secrets. However, it never explicitly says when to prefer this over sibling tools such as vault_documents or vault_fill, nor does it name alternatives or prerequisites.

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