Dantes Exchange

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

With no annotations, the description carries the full transparency burden and mostly succeeds: it says this is a pre-payment manifest lookup, explicitly says it is not for executing the scan, and details the return contents. It does not explicitly state that the call is read-only or free, nor does it mention auth/rate limits, which is a minor gap.

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

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

The description uses three labeled sections ('WHEN', 'NOT for', 'Returns') that front-load the most important information. Every sentence earns its place and nothing is wasted or redundant with the 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 one-parameter manifest getter with no output schema, it covers when to call, what not to do, and what will be returned. It is slightly incomplete on operational details such as whether the call itself costs or requires special access, though the pre-payment framing and endpoint-specific price hint mitigate this.

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

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

The schema only says id is a required string, while the description adds that it is a capability id and frames it as the lookup key for schema, price, and when-to-use. It does not specify the id's format or source, but for a single simple identifier this is sufficient.

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 opens with 'WHEN: Use when you already have a capability id and need schema, price, and when-to-use before paying,' which clearly states the verb, resource, and purpose. It also disambiguates from execution via 'NOT for: Do not use to execute the scan,' distinguishing it from invoke_capability.

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

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

It provides an explicit trigger condition ('already have a capability id ... before paying') and an explicit exclusion ('Do not use to execute the scan'). It does not name sibling tools like invoke_capability or search_capabilities directly, so the alternative routing is clear but slightly less explicit than it could be.

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 burden and does so well. It discloses that semantic and economic evidence are kept separate and never combined, that benchmark figures appear only where measured, and that missing economic measurement returns NOT_MEASURED rather than a borrowed value.

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 well organized with WHEN, NOT for, and Returns sections. Every sentence contributes essential routing or behavioral information, and the most important usage boundary is front-loaded.

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 tool with no output schema, the description adequately explains what the caller should expect, including the NOT_MEASURED fallback and the separation of evidence types. Some jargon like 'dated forward-return pack' and 'n, window, as-of' is not expanded, but the core invocation contract is sufficiently clear.

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

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

Schema coverage is 100% and the one parameter 'id' already has a description. The description references 'listed skill' which maps to the capability id, but it does not add meaningful format, source, or constraint details beyond the schema.

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

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

The description clearly identifies the tool as returning a dated forward-return pack for a listed skill, and the title supplies the 'get' verb and resource. The 'NOT for' clause explicitly distinguishes it from a live scan and from current-day hits, separating it 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?

The description gives an explicit WHEN condition ('need the dated forward-return pack for a listed skill') and explicit exclusions ('Do not use as a live scan... not today's hits'). It does not name sibling tools as alternatives, but the usage boundary is clear enough for an agent to route correctly.

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

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

With no annotations, the description fully carries the behavioral disclosure burden, and it does so thoroughly. It explains the x402 PaymentRequired flow, that nothing executes or is charged until payment verifies, and that a zero-result scan is still a billable completed run rather than an error.

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 well-structured with WHEN, NOT for, and Returns sections, and the key usage conditions are front-loaded. It is dense but every clause earns its place, though the phrasing 'the user wants names that match it now' is slightly awkward and the payment detail is lengthy.

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 tool with no output schema and no annotations, the description covers return shape, payment behavior, and key error semantics, which is quite complete. It could additionally point the agent to siblings for discovering capability ids or retrieving input schemas, but the sibling list already signals where to look.

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

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

The schema already documents both parameters at 100% coverage: id is the capability id and input is an object conforming to the capability's input_schema. The description adds no additional parameter-level meaning, but the baseline of 3 applies because the schema covers the needed semantics.

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

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

The description clearly indicates this tool runs a selected listed skill/capability to produce matching names, and it explicitly excludes quotes, news, and unlisted setups. It does not state the core action in a single direct 'invoke this capability to return names' sentence, but the WHEN guidance makes the purpose sufficiently 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?

The description gives explicit WHEN conditions — chosen skill, user wants names now, ready to pay — and explicit NOT-for exclusions such as quotes, news, and unsupported patterns. It does not name sibling alternatives like search_capabilities or get_capability for finding a listed capability, but the usage context is otherwise clear.

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 behavioral disclosure burden. It usefully discloses return semantics: published datasets with as-of dates, universes, and the member ticker list when a `universe` is supplied. It also adds a meaningful negative guarantee that raw dataset files are never returned, which is not inferable from the schema.

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

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

The description is well-structured with WHEN, NOT for, and Returns sections, and every sentence earns its place. It is front-loaded with the most important usage context and contains no filler.

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

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

Given the rich schema and optional parameters, the description provides enough context for an agent to know when to call the tool and what to expect back, especially since there is no output schema. It omits details like pagination behavior, rate limits, or explicit read-only status, but these are secondary for a simple listing tool and partly derivable from the schema.

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

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

Schema description coverage is 100%, so the schema already documents all 7 parameters well, including the two enums. The description adds only a small amount of context around the `universe` parameter's effect, which largely duplicates the schema's own parameter 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 a specific action and resource: listing published datasets and enumerating their equity universes, optionally returning member ticker lists. It is unambiguous about what the tool does, though it does not explicitly differentiate itself from the sibling capability tools by name.

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 positive guidance ('Use when you need what universes / as-of books a skill can run on') and explicit negative guidance ('Do not use to fetch prices or news'). It stops short of naming alternative sibling tools, so it lacks the full when-not-to-use-versus-alternative routing.

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 the return shape (capability ids with price, run requirements, nested when/not_for/returns) and the notable not_encoded field. It does not mention side effects or pagination, but the read-only nature is implied by the 'NOT for running a scan' guidance.

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 organized into WHEN / NOT for / Returns blocks, each contributing distinct guidance. It is slightly wordy but efficient and front-loaded with the central trigger condition.

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

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

The description provides enough context for an agent to decide when to call search_capabilities and what to expect back, including the not_encoded caveat. However, it omits any definition of the category parameter and provides no example, which is a noticeable gap given the sparse schema.

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 explicitly define the query or category parameters. It implies query is the trader-language setup mentioned in WHEN, but category is completely undocumented, leaving an optional parameter ambiguous.

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 action—searching capabilities—and the trigger condition ('user named a setup in trader language'). It distinguishes itself from siblings like get_capability and invoke_capability by focusing on discovery/identification rather than retrieval or execution.

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 WHEN and NOT for sections explicitly state when to use the tool and what not to do ('Do not use to run a scan or to invent a skill'). It does not name sibling alternatives directly, but the exclusion is clear enough to guide tool selection.

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