Picsart GenAI

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

Annotations already indicate destructiveHint true and readOnlyHint false. The description adds context: auto-picks newest model, spends credits, requires auth, and details the output structure including the resource_link block, going well beyond annotations.

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 a clear purpose statement, usage guidelines, parameter details, example, and output structure. While comprehensive, it avoids unnecessary repetition and flows logically. It could be slightly shorter but remains 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 the tool's moderate complexity (3 params, no enums, has output schema), the description covers all aspects: required inputs, optional parameter, output format with example, behavioral notes (auto-pick model, credits), and exclusions. No gaps remain.

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 provides 100% description coverage for the three parameters. The description adds meaning by specifying that 'image' must be a publicly accessible URL (not a local file), and explains the 'model' parameter's behavior (auto-pick unless overridden).

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: 'Replaces the background of an image with a new scene described by a prompt, keeping the foreground subject intact.' It also distinguishes from siblings by naming alternatives for removal, enhancement, vectorization, and generation.

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 provides when to use (e.g., 'change the background to X', 'put this on a beach') and when not to use, listing specific sibling tools (picsart_remove_bg, picsart_enhance, picsart_vectorize, picsart_generate) with their correct purposes.

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=true and destructiveHint=false. The description adds valuable behavioral details: 'pick one model per film', 'generate each Shot (capped at the model max duration)', 'optionally continue a shot from the previous shot's last frame', and 'save the film into a Cinema Studio folder'. This provides richer context beyond annotations, though it doesn't mention rate limits or auth specifics beyond 'no credits, no auth'.

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, efficient paragraph that packs all critical information: purpose, usage, behavioral details, and return value. Every sentence adds value with no filler. It is front-loaded with the main action and use case.

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 has no parameters, read-only behavior, and an output schema (mentioned in description returning `{ items, total, truncated }`), the description covers everything needed. It explains the function, the workflow, constraints, and output format completely.

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 has 0 parameters and 100% schema coverage. The description states 'Takes no input.' which is sufficient. According to guidelines, 0 parameters have a baseline of 4, and the description adds clear confirmation.

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 opens the Picsart Cinema Studio for building longer videos as sequences of shots. It specifies the verb 'opens', the resource 'Cinema Studio', and the exact use case ('make a longer video, a multi-shot clip, or a short film'). This distinguishes it from sibling tools like picsart_music_studio and picsart_generate by focusing on multi-shot video composition.

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 explicitly says 'Use when the user wants to MAKE a longer video, a multi-shot clip, or a short film.' This provides clear context for when to use the tool. However, it does not provide explicit when-not-to-use instructions or directly contrast with sibling tools, though the specificity implies alternatives.

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, destructiveHint. Description adds valuable behavioral context: breakdown of resettable/accumulative/overdraft, meaning of nextResetDate, and that it takes no input. No contradictions.

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?

Description is well-structured and front-loaded with main purpose. Every sentence adds value, explaining fields and usage context without redundancy. Appropriate length for the tool's 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?

Fully explains all return fields and their semantics, even though an output schema exists. Provides guidance on integration with sibling tools (picsart_generate, picsart_preflight). Complete for a zero-parameter, read-only 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?

No parameters; schema coverage is 100% (empty). Description correctly states 'Takes no input.' Baseline for 0 params is 4, and no further param info 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?

Clearly states it returns the current Picsart credit balance, distinguishing from sibling tools like picsart_generate and picsart_preflight. The verb 'Returns' and resource 'credit balance' are specific.

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 states when to use: before expensive operations to warn low balance, or after a 402 from picsart_generate. Also clarifies when not to use: not for cost estimation (use picsart_preflight). Provides alternatives.

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 include destructiveHint: true, which the description confirms by detailing delete/move/update actions. It adds valuable context: soft-deletes go to trash unless permanent, every action returns current folder listing, and requires Authorization header. No contradictions with annotations.

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 but well-structured with bulleted actions and clear labeling. It front-loads the purpose. However, some redundancy (e.g., repeating 'Requires Authorization') could be trimmed. Still efficient overall.

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 complexity (16 parameters, multiple actions, nested objects) and presence of output schema, the description covers all needed aspects: return values (e.g., result.url for upload), pagination, sorting, and nuances like data URI handling. No gaps identified.

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 only 25%, but the description compensates thoroughly. It explains parameter behavior per action: e.g., folderUid defaults to root, flat:true omits folders, upload accepts file or url, etc. This far exceeds the schema's minimal 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 it is a 'Single entry point for the authenticated user's Picsart Drive' and enumerates specific actions (list, create_folder, etc.). It distinguishes from sibling tools (all focused on image generation/editing) by being a file management tool.

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 explicit when-to-use instructions for each action (e.g., 'list: browse a folder', 'upload: save a file'). It does not explicitly state when not to use, but the context of sibling tools makes alternatives clear. Minor exclusion of non-use cases.

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?

Despite annotations already indicating destructiveHint=true and readOnlyHint=false, the description adds behavioral context: it spends credits, requires authorization, auto-selects the newest model, and lists effects (sharpen, denoise). No contradiction with annotations.

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 is purposeful. Front-loaded with core action, then negative guidance, parameter details, example, return format, and finally credits/auth. No superfluous 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?

Given the tool has 3 parameters and an output schema, the description fully covers purpose, usage, parameters, output fields, and constraints. It also explains credit spending and authorization, making it self-contained.

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 description adds beyond schema: clarifies image must be publicly accessible URL, model is an override, and scaleFactor is upscale ratio. Includes an example call, which further clarifies 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 clearly states the tool upscales and enhances images by sharpening, denoising, and raising resolution. It distinguishes from siblings by explicitly listing tools not to use for background removal, SVG conversion, or generation.

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 explicit when-to-use scenarios (e.g., 'upscale', 'enhance', 'make it higher resolution') and when-not-to-use alternatives (e.g., 'use picsart_remove_bg' for background removal). This is comprehensive and actionable.

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?

Beyond annotations (destructiveHint=true, etc.), the description discloses critical details: credits are spent, results are saved to Drive when enabled, return format includes multiple data types and resource links, authentication via Bearer token is required, and rendering behavior for ChatGPT. This significantly surpasses annotation-only information.

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 lengthy (~400 words) but well-organized: core function, workflow, exclusions, parameters, examples, return format, side effects, and auth. It earns its length given the tool's complexity, though a slightly more concise presentation would 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?

Given 16 parameters, nested objects, output schema present, and model-dependent variability, the description covers all essential aspects: purpose, usage guidance, parameter semantics, examples, return format, side effects, and authentication. It is fully adequate for an agent to invoke the tool correctly.

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 covers 100% of parameters with descriptions, but the description adds value by grouping required vs. model-dependent optional parameters, providing two concrete examples, explaining the 'extra' free-form record, and clarifying the 'async' parameter's intended use. This extra context raises the score above the baseline of 3.

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 runs any Picsart AI model to produce image/video/audio results, and explicitly lists operations for which dedicated tools exist (e.g., background removal, enhancement), preventing misuse. This distinguishes it from 12 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?

Provides a recommended workflow (list_models → model_params → preflight → generate) and explicitly states when NOT to use this tool: for editing operations with dedicated tools, validation, quoting cost, or browsing catalog. This gives agents concrete decision rules.

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?

Beyond annotations (readOnlyHint, idempotentHint, etc.), the description details the return formats for running ('ACCEPTED'/'IN_PROGRESS' with progress) and completed states ('COMPLETED' with payload or error), plus auth requirements. No contradictions.

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 concise, front-loaded with the primary purpose, and efficiently structured. Every sentence adds value, with no redundancy or unnecessary 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 the tool's simplicity and the presence of a detailed output schema (not shown), the description covers essential use context, parameter intent, return types, and authentication. It is fully sufficient 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 coverage is 100%, and the description adds context: 'job' is explained as the job handle, 'model' as the model ID, 'prompt' as echoed metadata, 'saveToDrive' as mirror of original call. This adds significant meaning 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 states the tool checks a generation job started by 'picsart_generate' with 'async: true'. It distinguishes itself from the synchronous use case, making the purpose specific and 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?

The description explicitly says 'widgets poll this every few seconds' and 'assistants normally call `picsart_generate` synchronously and never need this tool', providing clear guidance on when to use and when not to use the 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?

Annotations declare readOnlyHint, idempotentHint true, destructiveHint false. Description adds that the tool is read-only, spends no credits, and works without authentication. No contradiction, and extra behavioral context is provided.

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 long but every sentence serves a purpose. It is front-loaded with the main action, then provides usage guidance, parameter details, and behavioral notes. No fluff or redundancy.

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 complexity (8 optional params, widget rendering, return structure), the description covers usage context, alternatives, behavior, parameter semantics, and output format. Output schema exists and explains items/total/truncated, so no need to re-describe.

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% (all properties have descriptions). Description adds explanation of inputType codes and an example filter usage, which adds value beyond schema. However, the schema already provides enums and descriptions, so the extra is marginal.

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 lists Picsart AI models across all modes (image/video/audio) and renders a UI widget for user selection. It distinguishes itself from siblings like picsart_list_image_models by noting cross-mode searches.

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 tells when to use (user wants to see models, cross-mode searches) and when not to use (prefer dedicated tools for known modes, not for single model schema or cost estimation). Names alternative tools like picsart_list_image_models, picsart_model_params, etc.

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?

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), description adds that it is read-only, spends no credits, works without authentication, and explains the truncated field behavior. No contradictions with annotations.

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?

Well-structured and front-loaded with purpose, usage, and alternatives. However, it is somewhat lengthy with detailed parameter explanations; could be slightly more concise while retaining completeness.

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 8 optional parameters, 100% schema coverage, and presence of output schema, the description fully covers functionality, return shape (items, total, truncated), and constraints. No gaps for agent decision-making.

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%, but description adds significant value: explains inputType codes (t2i, i2v, etc.), provides an example filter, and describes the concise parameter default behavior. Goes well beyond 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 clearly states the tool returns the Picsart AI model catalog as plain data without UI, distinguishing it from sibling picsart_list_models which renders a picker. Uses specific verb 'Returns' and resource 'Picsart AI model catalog'.

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 states when to use (assistant reasoning, model selection, comparison) and when not to use (fetching params or cost estimate), with direct references to alternative tools picsart_model_params and picsart_preflight.

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=true and idempotentHint=true. The description adds valuable behavioral context: it is read-only, spends no credits, works without authentication, and describes the exact return structure. No contradiction with annotations.

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?

Concise and well-structured: starts with primary purpose, then usage guidelines, an example, and return format. Every sentence is informative and 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?

Given the low complexity (single parameter, output schema described), the description is complete. It covers what the tool returns, how to use it, prerequisites, and relationships to sibling 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 coverage is 100% (single parameter 'model' with description). The description adds an example and clarifies that the model id is required, providing extra context beyond the schema. Baseline 3, elevated to 4 due to added 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?

Clearly states the tool returns the parameter schema for a specific Picsart model, using a specific verb ('Returns') and resource ('parameter schema'). Additionally, it distinguishes itself from siblings like picsart_list_models and picsart_preflight by specifying what it is not for.

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 explicit guidance on when to use this tool (after getting a model id, to construct params for picsart_generate or picsart_preflight) and when not to (do not use to discover models or estimate cost, listing alternative 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?

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description confirms 'Read-only; spends no credits and works without authentication,' and describes the return format { items, total, truncated }. No contradictions; adds safety and authorization context.

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 that efficiently front-loads the main purpose, lists features, states exclusions, and ends with return format and safety notes. Every sentence adds value with no redundancy.

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 (multiple models, features) but no parameters and an existing output schema, the description fully covers purpose, usage scope, limitations, return type, and safety. It leaves no ambiguity.

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 has 0 parameters, and the description explicitly states 'Takes no input.' With 0 parameters, baseline score is 4, and the description appropriately confirms the absence without needing further detail.

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 opens the Picsart Music Studio for making music, songs, soundtracks, jingles, and sound effects, listing specific capabilities. It distinguishes from siblings by stating what it does not do (e.g., no editing, TTS, image generation).

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 explicitly says 'Use when the user wants to MAKE music...' and lists exclusions like 'Does NOT edit existing audio' and 'not for text-to-speech / voice cloning.' It also notes it takes no input and is read-only, guiding appropriate 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?

Annotations indicate readOnly, idempotent, non-destructive. Description adds that it does not charge, returns validation results always, and credits only when available and authenticated. No contradictions.

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 paragraph but packed with useful information, front-loaded with purpose. Could be slightly more structured but 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?

Covers all aspects: purpose, when/not to use, required inputs, example, return format. Output schema is described. Complete given 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?

Schema coverage is 100% with descriptions. The description adds value by explaining that params should include prompt, providing an example, and detailing validation and pricing behavior.

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 is a pre-flight check for picsart_generate, validating params and quoting credit cost without running the model. It distinguishes from siblings picsart_model_params (parameter lookup) and picsart_generate (actual generation).

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 states when to use (after assembling params, before generating) and when not to use (using picsart_model_params or picsart_generate). Also lists required inputs and provides an example.

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 indicate destructiveHint=true and readOnlyHint=false. Description adds that it auto-picks model, spends credits, requires Authorization, and returns specific fields. No contradictions.

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?

Front-loaded with main purpose, well-organized into clear sections: purpose, usage, exclusions, requirements, optional params, example. Every sentence adds value.

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 complexity, schema coverage, annotations, and output schema, the description covers input constraints, output format, credit usage, authentication, and model selection. Fully 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?

Schema coverage is 100% but description adds value: explains model is optional (auto-picks), image must be public URL not local, and shows example. OutputFormat mention reinforces its purpose.

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?

Clearly states it removes background and returns transparent cutout. Distinguishes from siblings like picsart_change_bg, picsart_enhance, etc.

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 when to use (user asks to remove background, cut out subject, make transparent) and when NOT to use (replace background, upscale, vectorize, generate). Also provides context on model selection and input requirements.

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 automatic model selection, best use cases, poor performance on photos, credit spending, required authentication, and return structure. Annotations (destructiveHint=true, etc.) are consistent and complemented by these details.

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 thorough but not excessively wordy; each sentence serves a purpose. It is front-loaded with the main action and then provides necessary details. Slightly verbose but still 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 the presence of an output schema (not shown but referenced), the description still covers input requirements, optional parameters, behavioral notes, return structure, and special scenarios (e.g., poor vectorization of photos). No gaps identified.

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 has 100% coverage, so baseline is 3. The description adds context for 'image' (must be public URL, not local file) and 'model' (overrides auto-pick), which provides meaningful guidance beyond 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 states 'Converts a raster image (PNG, JPG) into an SVG vector' with specific triggers ('vectorize', 'convert to SVG', etc.) and clearly distinguishes from siblings by listing tools to avoid (e.g., picsart_remove_bg, picsart_enhance).

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 when to use this tool, provides example user queries, and lists when not to use it with specific alternative tools, such as 'Do NOT use this to remove the background (use picsart_remove_bg)'.

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