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List Pollinations Models

pollinations_list_models
Read-onlyIdempotent

List Pollinations image and video models with filters for modality, pricing, capabilities, and search to choose the right model before generation.

Instructions

List currently available Pollinations image and video models from /image/models. Results are cached in memory for 15 minutes, so repeated calls are fast. Use this before generation when model choice, pricing, modality, reference-image support, end-frame support, or audio support is unclear. This tool does not require POLLINATIONS_API_KEY. Args: - modality (string, optional, default all): all, image, or video. Use image before image generation/editing. Use video before video generation. - search (string, optional): Case-insensitive search across model names, aliases, brands, descriptions, pricing, capabilities, and raw metadata. Examples: 'gpt', 'transparent', 'end_frame', 'audio', 'seedance', 'banana', 'edit'. Do not use search='cheap' to find cheapest; inspect the Pricing lines instead. - limit (number, optional, default 50, max 100): Maximum number of models to return. - detail (string, optional, default summary): summary returns compact model cards; full returns richer metadata for listed models. For one model, prefer pollinations_get_model_details. - sort_by (string, optional, default default): default, name, or price. Use sort_by=price and sort_order=asc to find cheaper models. - sort_order (string, optional, default asc): asc or desc. - paid_only (boolean, optional): Filter by paid_only flag. - supports_reference_images (boolean, optional): true returns models with max_reference_images > 0. - supports_end_frame (boolean, optional): true returns video models with end_frame capability. - supports_audio (boolean, optional): true returns models that output audio or support audio_output. - refresh (boolean, optional, default false): Bypass the 15-minute in-memory cache and refetch /image/models. - response_format (string, optional, default markdown): markdown for readable summaries, json for structured compact/full metadata. Returns: Compact model names, category, pricing, input/output modalities, and key capability flags by default. Use pollinations_get_model_details for complete raw metadata for one model. Examples: Cheapest images: modality=image, sort_by=price, sort_order=asc, limit=5. Cheapest videos: modality=video, sort_by=price, sort_order=asc, limit=5. First/last-frame videos: modality=video, supports_end_frame=true. Image editing/reference models: modality=image, supports_reference_images=true. Error handling: If no models match, retry with modality=all, remove search, or remove capability filters. Use refresh=true only when you need current model changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of models to return.
detailNosummary returns compact low-context model cards. full returns richer metadata for listed models. Use pollinations_get_model_details for one model's full raw metadata.summary
searchNoOptional case-insensitive search across names, aliases, brands, descriptions, capabilities, pricing, and metadata. Examples: gpt, transparent, end_frame, audio, edit, seedance, banana. Do not use cheap as a search term; inspect Pricing instead.
refreshNoBypass the 15-minute in-memory cache and refetch the Pollinations model catalog.
sort_byNoSort models by default API order, name, or lowest numeric pricing value.default
modalityNoFilter models by modality: all, image, or video. Use video before video generation and image before image generation/editing.all
paid_onlyNoOptional paid_only filter. true returns paid-only models; false returns models not marked paid-only.
sort_orderNoSort direction for name or price sorting.asc
supports_audioNoOptional filter for models that output audio or support video audio_output.
response_formatNoMCP response format: markdown for readable summaries, json for raw model metadata.markdown
supports_end_frameNoOptional filter for video models with end_frame capability.
supports_reference_imagesNoOptional filter for models with max_reference_images greater than zero.
Behavior5/5

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

Beyond annotations (readOnly, idempotent), the description discloses 15-minute in-memory caching, no API key requirement, refresh behavior, and error handling guidance. This adds meaningful operational context without contradicting the annotations.

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

Conciseness4/5

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

The description is fairly long but organized into Args, Returns, Examples, and Error handling, with a clear first sentence. Minor redundancy exists (e.g., the 'prefer pollinations_get_model_details' advice appears twice), so it is not perfect, but it earns its detail.

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

Completeness5/5

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

Given no output schema, the description explains return content ('Compact model names, category, pricing, input/output modalities, and key capability flags'), provides worked examples for common queries, and covers error handling. For a 12-parameter list tool with caching and various filters, this is fully sufficient.

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

Parameters5/5

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

Although the schema covers all 12 parameters, the description enriches them with practical guidance: e.g., 'Use sort_by=price and sort_order=asc to find cheaper models,' and warns against using 'cheap' as a search term. It also maps filters to use cases like reference-image support and end-frame videos.

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

Purpose5/5

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

The description opens with a specific verb and resource: 'List currently available Pollinations image and video models from /image/models.' This clearly distinguishes it from sibling tools like pollinations_generate_image or pollinations_get_model_details.

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

Usage Guidelines5/5

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

It explicitly states when to use: 'Use this before generation when model choice, pricing, modality, reference-image support, end-frame support, or audio support is unclear.' It also provides exclusions ('Do not use search='cheap'') and points to alternatives ('For one model, prefer pollinations_get_model_details').

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

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