inkflow

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?

Discloses that writing starts automatically after payment clears, returns a Stripe payment URL, and progress is available via inkflow_job_status and webhooks. No annotations exist, so description covers key behaviors well.

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 core purpose and outcome. Every sentence adds value; no 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?

Covers payment flow, automation, and progress tracking. With no output schema, it mentions the return format (Stripe URL). Highly informative for a 13-parameter tool, though some parameters remain undetailed.

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?

Adds meaningful context beyond schema for 'premise', 'brief', 'attachments', and 'contentRules'. Schema coverage is 46%, and description compensates by clarifying purpose and constraints for several 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?

Describes a specific action: placing a paid order for books/manuals/specs/series. Distinguishes from siblings like inkflow_quote (which likely provides quotes) and inkflow_capabilities.

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?

States the requirement of an apiKey and registration URL. Implies use when ready to order, but does not explicitly exclude using inkflow_quote first or when not to use.

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 provided, so the description carries the burden. It discloses behavioral traits: '3x-margin fixed pricing' and 'quotes honoured for 24h', which are helpful. It does not mention auth or rate limits, but for a quote tool this is adequate.

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. First sentence establishes purpose and contrast with ordering; second adds key constraints. Front-loaded and efficient.

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 5 parameters (1 required) and no output schema, the description covers the general purpose but omits details like output format (quote structure), parameter relationships, or error handling. It is somewhat incomplete for an AI agent.

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 40%, and description adds general context (pricing, validity) but does not explain individual parameters beyond what schema already provides (e.g., wordTarget, seriesBooks have schema descriptions). Some parameters lack 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 clearly states 'Firm price quote for a writing job WITHOUT ordering', specifying the tool's function (providing a quote) and distinguishing it from the ordering tool. It also adds context like fixed pricing and 24-hour validity.

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 contrasts with ordering, implying use for quotes before ordering. However, it does not explicitly list when to use or not use this tool, nor name alternatives. The sibling tool 'inkflow_order' is implied as the alternative.

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 full burden. It discloses the commission nature, training dependency on face selection, delivery of a .safetensors file, perpetual license, and pricing. This is transparent, though exact training duration is not specified.

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 three sentences, front-loaded with the main action and quickly covers key details. It is dense but not overly verbose; a minor rewrite could improve clarity.

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, but the description explains the outputs (LoRA file, reference pack, license) and the ordering workflow. It is complete for a commission tool, though it lacks error or rate limit information.

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 only 20% (actorBrief described). The description adds context for actorBrief ('age, look, build, style — the person you need') and implies apiKey is required, but does not describe other parameters like currency or webhookUrl. It partially compensates for low 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 clearly states the tool commissions a custom ULTRA-trained LoRA digital actor, specifying the process, deliverables (LoRA file, reference pack, license), and constraints (synthetic person, $48 flat). It distinguishes from siblings like inkflow_choose_actor_face.

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 the workflow: ordering leads to candidate thumbnails, then training via inkflow_choose_actor_face. It implies when to use this tool, but does not explicitly exclude alternatives or state when not to use.

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