inkflow

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

With no annotations, the description carries the burden. It clarifies the tool is a read operation ('Check') and gives useful context on how credits work (instant settlement, no checkout). It doesn't disclose response format or error behavior, but those are minor for a simple balance check.

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

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

Two sentences, front-loaded with the purpose. The second sentence adds valuable context about how credits are used and points to the top-up tool. No word wasted.

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

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

Given no output schema and no annotations, the description does a good job explaining the tool's role in the workflow. It covers purpose, usage context, and the related top-up tool. It does not describe the return format, but for a simple balance check this is a minor 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 coverage is 0%, so the description must compensate. It mentions 'your INKFLOW API key' which indicates the parameter's role, but provides no additional detail about the key's format or where to obtain it. The single parameter is self-explanatory, but the description could do more to fully compensate for the lack of 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 'Check' and a clear resource 'credit balance on your INKFLOW API key'. It distinguishes itself from siblings like inkflow_topup (topping up) and inkflow_quote (quoting), and the purpose is immediately obvious.

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 explains when to use the tool: to ensure you have credits before placing an order. It also explicitly points to inkflow_topup as the alternative when you need more credits, providing clear guidance on when to choose this versus a 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 provided, the description carries full burden. It discloses that the tool is read-only (returns products and prices), mentions machine-audited quality, delivery time (<24 hours), and notes that book-to-movie adaptation is not currently orderable. This provides behavioral context beyond a simple listing.

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 relatively long but each sentence adds valuable information, such as types of works, quality assurance, and availability. It front-loads the main purpose and is well-structured, though a slight reduction in extraneous details could be made for conciseness.

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

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

Given no output schema and only one input parameter, the description provides comprehensive context about what the tool returns, including pricing, genres, languages, and special features like LoRAs. It also clarifies what is not available, making it complete for an agent to understand the tool's capabilities.

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 for the single parameter (currency) is 100%. The description mentions 'in the requested currency' but adds no additional meaning or constraints beyond what the schema already provides. Baseline 3 is appropriate as the schema carries the definition.

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 that the tool returns INKFLOW's full catalogue including products, tiers, genres, languages, and prices. It lists specific types of works (full-length books, multi-volume series, manuals, LoRAs) and distinguishes itself from sibling tools like inkflow_order and inkflow_quote by focusing on listing capabilities rather than ordering or training.

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 browsing the catalogue and getting pricing, but it does not explicitly state when to use this tool versus alternatives. There is no mention of when-not-to-use or specific prerequisites, leaving the agent to infer context from sibling tool names.

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 discloses the key behavioral trait that training starts immediately upon selection, but does not mention idempotency, rate limits, failure modes, or other potential side effects.

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 that conveys the action and consequence without extraneous words. Every part is meaningful.

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 simple tool with 3 required params, no output schema, and no annotations, the description provides the core context but omits details on what 'orderId' and 'apiKey' represent and what the response looks like after selection.

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 33% (only 'choice' has a description). The description adds context by linking the parameters to 'candidate thumbnails' and 'training starts', but does not explain 'apiKey' or 'orderId' beyond their names. This is adequate but not highly informative.

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 verb 'Pick', the resource '3 candidate thumbnails', and the consequence 'ULTRA LoRA training starts'. It distinguishes from sibling tools like inkflow_train_ultra_lora_actor by indicating this is a prerequisite selection step.

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 implicitly conveys when to use: after obtaining candidate thumbnails, before training. However, it does not explicitly state when not to use or provide direct comparison to alternatives like inkflow_train_ultra_lora_actor.

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, description adequately discloses free usage, no key requirement, and nature of samples. No mention of side effects or additional constraints, but for a simple read-only tool this is sufficient.

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?

Single sentence, front-loaded with 'FREE, no key needed'. Every phrase adds value, no wasted words.

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

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

Given zero parameters, no output schema, and no annotations, the description fully explains the tool's purpose and output (samples). Complete for its simplicity.

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?

No parameters in schema (0 params, 100% coverage). Description adds no parameter info, but baseline 4 is appropriate as no compensation needed.

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 clearly states the tool provides free samples of ULTRA LoRA actor cards, object/set LoRA renders, and product spec sheets to evaluate quality before ordering. Verb 'see' implies retrieval, resource specified. Distinct from sibling tools like inkflow_order or inkflow_train_ultra_lora_actor.

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?

Indicates free, no key needed, and purpose is to see quality before ordering. Implies usage context (pre-purchase evaluation) but lacks explicit exclusions or alternative suggestions.

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 exist, so the description must carry full behavioral disclosure. It mentions live status but omits read-only nature, permission requirements, error handling, or response format. Minimal useful context beyond output content.

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 one sentence, highly concise, and front-loads the tool's purpose. Every word contributes value, but it could briefly elaborate on parameters.

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 status tool, the description covers the main output but lacks details on input format and error scenarios. No output schema means more description weight, yet this is partially adequate.

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

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

Schema coverage is 0%, and the description adds no meaning to parameters (apiKey, orderId). These are left undefined, requiring the agent to infer from names, which may be 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 clearly states the tool provides 'Live status of an order' and lists specific content (chapters, QA, delivery links), distinguishing it from sibling tools like inkflow_order. The verb 'status' and resource 'order' are explicit.

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 use for checking order status but does not explicitly state when to avoid it or suggest alternatives among siblings. Context is clear but no exclusions.

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

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: instant settlement with credit, Stripe payment URL otherwise, automatic writing start after payment, per-chapter progress via inkflow_job_status, and webhooks. It also mentions the requirement for an API key. This is substantial behavioral transparency.

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

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

The description is a single paragraph but packed with information. It's front-loaded with the main purpose and then details. It's somewhat long but every sentence adds value. It could be slightly more structured, but it's not overly verbose.

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

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

Given the tool's complexity (14 parameters, multiple product types, payment flow), the description covers the essential flow: order placement, payment, and post-payment actions. It doesn't explain return values (no output schema), but it mentions progress tracking via inkflow_job_status. It's fairly complete for a complex 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 50%, so the description must compensate. It explains the 'premise' parameter (what to write, actor brief) and mentions 'brief' as supporting text. It also clarifies the 'product' enum by listing product types in the description. However, it doesn't detail all 14 parameters, but the schema covers many. The description adds value for key parameters like premise and product.

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

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

The description clearly states the tool's purpose: placing a paid order for a variety of products (books, audiobooks, videos, etc.). It uses specific verbs ('Place a paid order') and enumerates the product types, distinguishing it from sibling tools like inkflow_quote (for quotes) and inkflow_job_status (for 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 provides clear context on when to use this tool: when placing a paid order. It also mentions the instant settlement condition (key credit + GBP quote) and the alternative (Stripe payment URL). It doesn't explicitly state when NOT to use it, but the context is clear enough given the sibling tools.

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

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

No annotations are provided, so the description bears the burden. It hints at non-destructive behavior via 'WITHOUT ordering' and mentions quote validity, but doesn't disclose permissions, side effects, or rate limits.

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

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

The description is two sentences, front-loaded with the purpose, and efficiently conveys pricing details without unnecessary fluff.

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

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

It covers quote validity and pricing, but doesn't explain parameter usage, required fields, or the full quote process. Given the schema's complexity, the description leaves gaps in understanding how to use the tool effectively.

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

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

The description provides pricing context (writing vs. media) but doesn't map these to specific parameters. Some schema descriptions exist (wordTarget, seriesBooks), but others like product and currency are unexplained, and the description doesn't clarify their roles.

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 it provides a firm price quote without ordering, and specifies the covered domains (writing, audio, video). It effectively communicates the tool's core function.

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 explicitly says 'WITHOUT ordering', distinguishing it from the ordering tool, and implies it's for price inquiries. However, it doesn't explicitly mention when to use it versus other tools beyond this contrast.

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 full burden and does so exceptionally well. It discloses revenue splits (85% set sales / 25% production), instant credit vs monthly payout, verification from file headers, human review process, and strict content policy. This far exceeds typical disclosure and covers the key behavioral expectations.

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 longer than average but each sentence provides relevant operational context: action, revenue terms, verification, review, and content policy. It is front-loaded with the action and uses a natural sentence structure. Slightly verbose due to financial details, but not wasteful.

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 explains the business and verification context thoroughly, but because there is no output schema, it should clarify what the API returns (e.g., listing confirmation, review status, listing IDs). It also does not mention the mechanics of how the tool identifies which LoRA sets to list beyond the apiKey. This leaves operational 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?

The only parameter is apiKey, yet the description never mentions it. Schema coverage is 0%, so the description was expected to compensate, but it does not explain the authentication context or any additional meaning. The parameter name is self-explanatory, but the description adds no semantic value.

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

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

The description clearly states the action: "LIST YOUR OWN TRAINED LoRA SETS FOR SALE on INKFLOW." This is a specific verb+resource pair (list/sell your trained LoRA sets) that distinguishes it from sibling tools like training or ordering. It leaves no ambiguity about what the tool does.

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

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

The description provides clear context: use this tool when you want to sell your own trained LoRA sets. It also specifies important preconditions (file headers verify steps/rank, human review before going live). However, it does not explicitly mention alternatives or when not to use it, so it lacks full exclusionary guidance.

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 transparently reveals that the tool returns a one-time checkout link for a human to pay, after which autonomous transactions proceed until balance runs out. This human-in-the-loop behavior is a critical trait not otherwise knowable, though it does not cover error conditions or auth requirements.

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

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

The description is two sentences with no filler, front-loading the primary action and then adding the key behavioral nuance. Every sentence adds value, and the structure is easily scannable for an AI agent.

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 2-parameter tool with no output schema or annotations, the description covers the essential context: the purpose, the human checkout flow, and the autonomous follow-up. It omits edge-case behavior like invalid apiKey or payment failures, but for the intended simplicity, the description is sufficiently complete.

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

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

The schema already documents gbp with a range, but apiKey has no description. The description's phrase 'your INKFLOW API key' adds meaning for the apiKey parameter, while 'Add credit' implies gbp is the amount. However, it does not explicitly clarify the format or units beyond the schema's '5 to 2000', so it only partially compensates for the 50% schema coverage.

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

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

The description explicitly states 'Add credit to your INKFLOW API key' with a specific verb and resource, immediately clarifying the tool's function. It also distinguishes itself from siblings by noting this is the only step needing a human, making its unique role among the listed tools 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 provides clear usage context by stating that this is the only step that requires a person, implicitly guiding when to use this tool. It does not explicitly name alternatives or when-not-to-use scenarios, but the context strongly implies it is for topping up credit, distinct from balance checks or order placement.

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?

Without annotations, the description fully discloses key behaviors: '4,500+ step rank-64 multi-reference identity model,' the deliverables (LoRA file, reference pack, license), the synthetic-person guarantee, and the conditional start of training after face selection. This is far beyond typical descriptions and covers the user-relevant expectations.

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?

Every sentence delivers unique information: the model specs, what you get, the synthetic guarantee, the face-selection step, and the price. It is front-loaded with the purpose and contains no fluff, making it appropriately sized for the complexity.

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

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

The description covers deliverables, process, and pricing, but given no output schema, it fails to explain what the immediate API response contains (e.g., order ID, whether thumbnails are returned directly) or how delivery/tracking works via sibling inkflow_job_status. This leaves a moderate gap for an agent deciding how to invoke and interpret the result.

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 very low (20%) and the description does not compensate. It never mentions parameters such as apiKey, currency, actorName, or webhookUrl, and does not provide additional meaning for actorBrief beyond what the schema already states. The '$48 flat' hints at currency but does not clarify the parameter usage.

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

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

The description opens with a specific verb+resource ('Commission a custom ULTRA-trained LoRA digital actor') and details the product's specs, deliverables, and price. It clearly distinguishes this from sibling tools like inkflow_choose_actor_face and inkflow_order by outlining a unique multi-step workflow.

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 explains when to use this tool in the ordering pipeline: after ordering, the user gets thumbnails and then must use inkflow_choose_actor_face to proceed. It implies the tool is for commissioning custom LoRA actors, but does not explicitly state when not to use it or compare it to alternatives like inkflow_order.

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