Raploom

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

This goes beyond simple status flags. It clarifies critical flow details by stating 'No charge, Stripe session or video generation happens here' and instructs the agent exactly how to handle the payment link and what to do upon failure.

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 dense but highly efficient, front-loading the core action before detailing constraints, operational boundaries, and financial mechanics, all in one coherent block.

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 complexity—being an intermediate, non-destructive transactional step—the description covers the required lifecycle, payment mechanics, and failure conditions, making it maximally complete for the agent's use.

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?

Since schema coverage is 0%, the description must carry the entire burden. It defines constraints on characters (1–2, without photos), the payment structure (pricing based on offer), and the nature of the lyrics input.

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 starts with a direct and specific goal: 'Create an UNPAID order for 1–2 original characters, without photos.' This is clear and immediately distinguishable from sibling tools like `get_order_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?

It provides explicit prerequisites for use: 'ONLY call after the user explicitly approves the characters, four lyrics and delivery email.' It also guides behavior by stating, 'Do not automatically retry an uncertain order call.'

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?

Annotations already declare readOnly, non-destructive, non-idempotent, open-world behavior, so the safety profile is covered. The description adds genuinely new behavioral context: the operation is free, the result is a draft requiring user approval, and how lines are split between two performers — details an agent cannot infer from annotations or 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?

Three tight sentences, front-loaded with the core action and output shape, then the workflow constraint, then the edge case. Nothing is redundant.

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

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

With no output schema, the description usefully states the output is four lines and how to present them for approval. But it leaves the subject and occasion enums uninterpreted and gives no hint about what else the response contains, which matters for a five-parameter generative tool with zero schema descriptions.

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 carry the burden. It correctly disambiguates two parameters: performer count maps to line assignment (1–2 = A, 3–4 = B) and 'a recipient is not another singer' prevents conflating recipient with a second performer. However, topic, subject, and occasion receive no explanation at all, leaving three of five parameters undocumented in both schema and 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?

Specific verb and resource: 'Write four short English rap lyric lines', with the 'for free' qualifier that separates this drafting step from the paid ordering siblings (create_character_video_order). An agent can tell immediately this produces draft text, not a video order.

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?

'Treat them as a draft: show the words and let the user approve or edit before ordering' establishes the workflow position — this is a preview step that precedes ordering. It gives clear context but names no explicit exclusion beyond the implicit 'do not order yet'.

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?

Annotations already declare this as a safe read-only, idempotent operation. The description adds important context beyond annotations: the access token is required for authorization, only payment/video state and the private order link are returned, and video downloads remain on the website. These details materially affect how an agent uses and reports results.

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 compact sentences with no waste. The required credential pairing is front-loaded, followed by the prohibition and return scope, making the key constraints 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?

No output schema exists, so the description appropriately states what is returned: payment/video state and the private order link, with downloads excluded. Together with the explicit authorization requirement and usage prohibition, it is complete enough 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 carry parameter meaning. It explains that both parameters are required together and that the accessToken is returned at order creation, adding useful provenance and authorization semantics. It does not describe the orderId UUID format, but the schema already enforces that pattern.

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

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

States a specific verb and resource: read a private order. It distinguishes the operation by requiring both orderId and accessToken, and clarifies that alternative lookup by email is invalid. The return scope is also stated, so an agent can identify the tool without inspecting its schema.

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

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

Explicitly says to use BOTH orderId and accessToken returned at creation and explicitly says never to look up orders by email. This gives both the required invocation pattern and a clear exclusion, leaving little 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?

Annotations already declare readOnlyHint, idempotentHint and non-destructive, so the safety profile is covered. The description adds a genuine policy constraint (never accept photos here, consent handled off-tool), but says nothing about what the returned link is, whether it expires, or what happens if `stage`/`topic` are omitted.

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 short sentences, the use case comes first and the hard constraint follows. Nothing is filler, though the opening clause is grammatically tangled enough to slow comprehension slightly.

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

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

No output schema exists, so the description should explain what the link actually is and how the caller should present it; it only says 'website creation link'. Combined with the unexplained `stage` and `topic` parameters, an agent has to guess about most of the call's surface.

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 carry the load. It implicitly defines `kind` via 'one person / two separate people / a pet photo', but `stage` (five enum values) and `topic` (160-char string) are never mentioned, leaving two of three parameters entirely undocumented.

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?

Names a concrete output (a website creation link) scoped to three input cases, and the mapping 'one person / two separate people / a pet photo' corresponds to the solo/duo/pet enum values. Wording is a bit awkward ('give the user a website creation link') and it never says explicitly that it creates nothing itself, but an agent can tell it apart from create_character_video_order.

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?

Provides an explicit exclusion — photos, screening and consenting-adult declarations must happen on raploom.com and must never be accepted through this tool. That is a real when-not-to rule, though it does not disambiguate against sibling create_character_video_order or get_order_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?

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful context beyond that: the outputs are real published examples with actual lyrics, they should not be treated as guarantees, and 'Disclosures must stay visible' signals a compliance constraint. It does not describe return format or pagination, but the annotations carry the safety profile.

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 and front-loads the core purpose. Most sentences earn their place, though 'Disclosures must stay visible' is cryptic without domain context and slightly interrupts the flow.

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

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

For a simple read-only list tool with no output schema and one optional enum parameter, the description covers what is returned (real published outputs and lyrics), the key caveat, and the filter. It is complete enough to call correctly, with only minor ambiguity around the disclosure requirement.

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?

There is one optional enum parameter with 0% schema description coverage. The description only says 'Optional use filter,' which clarifies optionality and filtering purpose but does not explain the enum values beyond what the schema itself lists. This is minimal but adequate compensation for a single self-describing enum.

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 and resource: 'Show real published Raploom outputs and their actual lyrics.' This clearly distinguishes it from sibling tools like draft_lyrics, which creates lyrics rather than showing published examples. It does not explicitly name a sibling, but the purpose is unambiguous.

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

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

It gives a usage caution ('Use these to explain possibilities, not to promise an identical result') and notes the optional filter, but it does not state when to choose this tool over alternatives such as draft_lyrics or list_stages. Usage is implied rather than fully guided.

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?

Annotations already declare readOnly, idempotent, non-destructive behavior, so the safety profile is covered. The description adds a genuine domain rule (Hotel Lobby is limited to two adult photos) that cannot be derived from structured fields, but says nothing about the shape or ordering of the returned stage list.

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 with zero filler, and the core purpose is front-loaded ahead of the secondary constraint. Every clause carries 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?

For a zero-parameter, no-output-schema reference tool, the description covers what is enumerated and one important selection constraint. Only a brief note on how stages/photos modes are structured in the response would improve 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?

The tool takes zero parameters, so there is nothing to disambiguate and the baseline is 4. The description correctly avoids inventing parameter discussion for a parameterless call.

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

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

States a specific verb (List) and resource (the five stages and their supported photo modes), which is precise enough for an agent to know exactly what it returns. It is clearly distinguishable from siblings like get_order_status or list_examples, which serve different discovery needs.

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 rather than stated — an agent can infer this is a discovery/reference call, but there is no explicit 'use this before X' or 'do not use when Y' guidance relative to siblings. The Hotel Lobby caveat is a domain constraint on selection rather than a when-to-call rule.

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