polli — Pollinations CLI Skill

polli — Pollinations CLI

Thin wrapper around gen.pollinations.ai. Generates images, text, audio, video; transcribes speech; manages API keys, usage, quests, agents, and invite-only my-models.

If polli is not installed, run npm i -g @pollinations/cli@latest (provides the polli binary).

When to use this skill

User asks to generate an image / text / audio / video via pollinations
User mentions polli, pollinations, pollen, pollinations.ai
User wants to transcribe speech or run TTS
User asks about their pollen balance, usage, or API keys
User wants to browse or filter available models
User wants to inspect quests or manage invite-only my-models
User wants to create or update a hosted prompt agent

For agent-assisted login, use polli --json auth login --no-browser. Read stderr while the command runs and show the user the verification URL and user code so they can review access. On approval, stdout contains one JSON result: {"authenticated":true}. Tokens are stored locally and never included in that result.

Quick reference

| Intent | Command | |---|---| | Log in once | polli auth login | | Agent-assisted login | polli --json auth login --no-browser | | Store an existing key | printf '%s' "$POLLINATIONS_API_KEY" \| polli auth login --with-token | | Generate image | polli gen image "<prompt>" --output out.png | | Generate text | polli gen text "<prompt>" | | Text with stdin as context | echo "<ctx>" \| polli gen text "<question>" | | Describe an image (vision) | polli gen text "what is this?" --image <url> | | One-shot TTS | polli gen audio "<text>" --output speech.mp3 | | Speak out loud | polli gen audio "<text>" --play (uses afplay on macOS; ffplay/mpv/mpg123 on Linux) | | Generate video | polli gen video "<prompt>" --output out.mp4 | | Generate a 3D model | polli gen 3d "<prompt>" --output out.glb (or --image <url> for image-only models) | | Embed text | polli gen embeddings "<text>" ["<text2>" ...] (one vector per line; also reads stdin) | | Change a voice | polli gen voice-change talk.mp3 --voice nova | | Isolate speech | polli gen isolate interview.mp4 (strips music/noise) | | Speech + character timings | polli gen audio "<text>" --timestamps (also writes speech.mp3.json) | | Transcribe audio | polli gen transcribe path/to.mp3 | | Upload a local file | polli upload path/to.png (prints public URL) | | List all models | polli models | | Filter models by type | polli models --type image (text, image, audio, video, 3d, embedding) | | Model health + latency | polli models --stats (default 60m, --window <min>) | | Check balance | polli usage | | Developer earnings | polli earnings (--days <n>) | | List your quests + claim state | polli quests (filters: --open --claimable --claimed --coming-soon) | | Manage prompt agents | polli agents list | | Manage invite-only community models | polli my-models list | | Update the CLI | polli update (global installs only; npx/local get instructions) | | Connect a coding harness to Pollinations | polli harness <bloom\|dsh\|hermes\|opencode\|openclaw\|pi\|prime\|tgpt> on (available adapters: polli harness --help) | | Start a Linux sandbox (alpha) | polli sandbox create (--timeout <seconds> to keep it running without ssh, 0 until you pause or kill it; pollinations-large as the template for 4 vCPU and 8 GB; then list, logs <id>, timeout <id> <seconds>, pause <id>, kill <id>); the default template comes logged in, with the coding harnesses | | ssh / scp / rsync into a sandbox | ssh <sandbox-id>.polli | | Machine-readable output | append --json to any command |

Setup

One-time: polli auth login (device-flow; creates a key with profile, usage, and keys). To store an existing key, run printf '%s' "$POLLINATIONS_API_KEY" | polli auth login --with-token. Verify with polli auth status (or polli whoami). Override the stored key for a single command with --key <key>. Prefix any command with POLLINATIONS_ENV=staging to use staging; it keeps its own login, so run POLLINATIONS_ENV=staging polli auth login once.

Recipes

Generate an image to a file

polli gen image "a fox reading a book, studio ghibli style" --output fox.png

Defaults: tongyi-mai/z-image-turbo, 1024x1024. Without --output the file is image.<ext>, with the extension inferred from the response's Content-Type (tongyi-mai/z-image-turbo and black-forest-labs/flux.1-schnell return JPEG, so image.jpg); an explicit --output is used as given. Pick a different model with --model black-forest-labs/flux.1-schnell (see polli models --type image). For edits / img2img, pass one or more --image <url> flags — must be public http(s) URLs, local paths are rejected client-side. Only models that list "image" in input_modalities actually consume the flag — black-forest-labs/flux.1-schnell and tongyi-mai/z-image-turbo are text-only and will silently ignore --image. Find i2i-capable models with polli models --type image --json | jq -r '.[] | select(.input_modalities | contains(["image"])) | .name' (common choices: google/gemini-2.5-flash-image, black-forest-labs/flux.1-kontext-pro, prunaai/p-image-edit). To use a local file, upload it first with polli upload (see next recipe). Img2img models may treat --width/--height as a hint and keep the source aspect — check the output with file/ffprobe; if the aspect matters, pre-crop the source or crop afterwards.

Upload a local file to get a public URL

URL=$(polli upload cat.png)
polli gen image "make the cat purple" --image "$URL" --output purple.png

polli upload <file> streams one raw-file request to media.pollinations.ai (400 MiB max; 30-day lifecycle, refreshed by GETs once the object is at least 15 days old). Each upload receives a unique id. Human mode: URL on stdout and id/size/contentType on stderr. --json: full upload response on stdout. The returned URL is public (no auth to fetch) and works anywhere --image is accepted — gen image, gen video, etc.

Generate text

polli gen text "summarize the three laws of robotics"

Save to file: --output summary.txt. Use --system "<msg>" to set system prompt. For reasoning models, pass --reasoning low|medium|high to control reasoning effort. Only send --reasoning to models where reasoning: true in polli models --type text --json — the flag is not validated client-side, and non-reasoning models may silently accept it (openai), ignore it, or return a 400 (mistral).

Describe an image with a vision model

URL=$(polli upload selfie.jpg)
polli gen text "turn this person into a cartoon pet in one playful sentence" --image "$URL"

gen text --image <url...> attaches one or more public https URLs as an OpenAI-style multimodal message — repeatable for multi-image prompts. Local paths aren't supported; run them through polli upload first (see the upload recipe above). Only text models with "image" in input_modalities actually read the image — filter with polli models --type text --json | jq -r '.[] | select(.input_modalities | index("image")) | .name'. Non-vision models silently ignore the attachment. Good defaults: openai, gemini, claude.

Pipe stdin as context into text generation

cat README.md | polli gen text "what does this project do?"

stdin becomes context; the positional argument is the question.

Interactive chat session

polli gen chat --model openai/gpt-5.4-nano --system "you are a terse assistant"

Slash commands inside the session: /exit, /clear, /save <path>.

Text-to-speech

polli gen audio "hello world" --voice nova --output hello.mp3
echo "long script" | polli gen audio --voice nova --output out.mp3

Without --voice, the API uses the model's default voice. To discover the full live voice list, use the model registry: polli models --type audio --json | jq -r '.[].voices[]?' — each audio model entry includes its voices[] array. Format defaults to mp3; --format opus|aac|flac|wav to change. Accepts stdin (same as gen text). Add --play to save and then play the audio back (handy for narration/demos). Playback starts after the file is fully written, and the command blocks until playback finishes — if you want fire-and-forget, wrap in a subshell: ( polli gen audio "..." --play & ). Player on macOS: afplay; on Linux it tries ffplay, then mpv, then mpg123 in that order.

Generate music (elevenlabs/music-v2)

polli gen audio "lofi hip-hop beat" --model elevenlabs/music-v2 --duration 30 --instrumental --output track.mp3

Generate sound effects (elevenlabs/eleven-text-to-sound-v2)

polli gen audio "thunderclap with heavy rain" --model elevenlabs/eleven-text-to-sound-v2 --duration 5 --output thunder.mp3

Text-to-sound-effect via ElevenLabs (aliases: sfx, sound-effects). --duration 0.5–30s (omit to let the model pick). Billed per second of output (~$0.004/s, capped at $0.12 for a full 30s).

Multilingual TTS (elevenlabs/eleven-multilingual-v2)

polli gen audio "Bonjour, ceci est un test" --model elevenlabs/eleven-multilingual-v2 --voice rachel --output fr.mp3

Stable, lifelike TTS across 29 languages (aliases: multilingual-v2, eleven-v2) — a non-alpha alternative to the default v3.

Generate video

polli gen video "a spacecraft landing on mars" --model alibaba/wan-2.2-fast --duration 5 --output mars.mp4

Cheapest path: --model alibaba/wan-2.2-fast at ~$0.01/sec, fixed 5-second output (any --duration value is ignored — you always pay for and receive 5 sec). For image-to-video, pass --image <url> with a public HTTPS URL (local file paths and 404/rate-limited hosts will fail with a server error).

Flag support varies per model and is not enforced client-side. --duration, --aspect-ratio, and --audio are forwarded to the server but may be silently ignored — verified on wan-fast where duration is locked to 5s, --aspect-ratio 9:16 still returns 16:9, and --audio produces no audio track. Always inspect the output (file, ffprobe) before trusting a flag worked. Check polli models --type video --json for per-model capabilities.

Video is not tracked by --stats. polli models --type video --stats returns empty — the stats pipe only records text/image/audio events. To compare video models, fall back to polli models --type video --json and look at price/description fields. The same applies to --type 3d.

Generate a 3D model

polli gen 3d "a red fox" --output fox.glb
polli gen 3d --image https://media.pollinations.ai/abc --resolution high

--model defaults to hyper3d/rodin-2.5 for a text-only prompt and microsoft/trellis-2 once --image <url> is given (public http(s), upload local files first with polli upload) — trellis-2 is image-to-3D only and rejects a bare prompt. --resolution low|medium|high only affects trellis-2. The output extension is inferred from the response's Content-Type, not the model name: nvidia/asset-harvester returns a Gaussian Splat .ply, everything else returns .glb. hyper3d/rodin-2.5 and nvidia/asset-harvester require Paid Pollen.

Generate embeddings

polli gen embeddings "first text" "second text" --model google/gemini-embedding-2
printf 'first\nsecond\n' | polli gen embeddings          # one input per stdin line

Prints one JSON array per input, in input order, one per line (pipe/jq-friendly). --dimensions <n> (128-4096), --task-type (Gemini retrieval hint), and --input-type query|document (Cohere) are optional. --json prints the full response including usage.

Change or isolate a voice

polli gen voice-change talk.mp3 --voice nova --format wav
polli gen isolate interview.mp4

voice-change re-speaks a local audio file in another voice (preset name or ElevenLabs voice ID) — default output voice.<format>. isolate strips music/background noise from local audio or video, keeping only speech — default output isolated.mp3. Both upload the file as multipart form data; ElevenLabs requires at least 4.6 seconds of audio for isolation, shorter clips fail with the API's audio_too_short error.

Speech with character-level timestamps

polli gen audio "Hello world" --timestamps

Saves the audio as usual (speech.mp3 by default) and appends .json to its path for the alignment/normalized_alignment character timings. Only elevenlabs/eleven-v3, elevenlabs/eleven-flash-v2.5, and elevenlabs/eleven-multilingual-v2 support this — other models fail with the API's error message.

Transcribe audio to text

polli gen transcribe recording.mp3 --language en

Models: openai/whisper-large-v3 (default), elevenlabs/scribe-v2, assemblyai/universal-2, assemblyai/universal-3.5-pro. Accepts common audio formats (mp3, wav, m4a, flac, ogg); non-audio input (e.g. a .txt file) returns a clear 400 invalid_request_error: extension "txt" not supported — no need to pre-validate with file. Default output is the plain transcript on stdout as a single line (pipe-friendly). Use --json for structured output: whisper and AssemblyAI return timing data when requested through the API; scribe returns only {text: "..."} — use whisper or AssemblyAI if you need timing data. --language <ISO-639-1> (e.g. en, fr) is an optional hint that can improve accuracy for non-English or accented speech.

Discover models

polli models --type text              # text models only
polli models --type image --verbose   # with context length / pricing
polli models --stats                  # health + avg latency + err% (60m default)
polli models --stats --window 5       # last 5 minutes only

Use --stats before choosing a model. Caveat: the err% column counts 5xx only — a model can show 0.0% while having massive 4xx rates (auth, validation, etc.). For the full picture use --stats --json and read errors_4xx, errors_5xx, latency_p95_ms.

Pricing fields are per-token, not per-request. completionImageTokens: 0.000008 means each output image-token costs that much — a single 1024x1024 image from openai/gpt-image-1-mini lands at ~$0.008, not $0.000008. Flat-priced image models (black-forest-labs/flux.1-schnell, tongyi-mai/z-image-turbo) expose completionImageTokens as the whole-image price because they emit exactly one "token" per image. When in doubt, make one call and read the true cost from polli usage --history --limit 5 --json.

Check usage and balance

polli usage              # current pollen balance
polli usage --history    # recent individual requests
polli usage --daily      # daily cost summary
polli usage --daily --key polli-harness-claude --days 1   # cost of one harness key for the last day (`--model`, `--csv` filter/export both views; `--key` is repeatable)
polli earnings           # developer earnings total + per-entity breakdown (default 30d)
polli earnings --days 7  # rolling window
polli quests             # your quests + claim state (open/claimable/claimed/closed/coming)
polli quests --claimable # only rewards ready to claim

History is eventually consistent — a request you just made may not appear for 30–60s. When matching costs to freshly-generated media, use --limit 50 and filter by timestamp, and retry if the expected entry is missing. polli usage --json returns {"pollen": <number>} — the current balance only; use --history --json or --daily --json for cost breakdowns. Those print a JSON array of the API usage records (numeric cost_usd, api_key_id, available per-modality token fields), not the table columns.

Manage my-models

polli my-models list
polli my-models models --base-url https://api.example.com/v1 --bearer-token "$UPSTREAM_KEY"
polli my-models create --name my-model --title "My Model" --api chat_completions --url https://api.example.com/v1/chat/completions --bearer-token "$UPSTREAM_KEY" --upstream-model gpt-4.1-mini --required-safety privacy,secrets,sexual,violence,shield
polli my-models create --name my-image --title "My Image" --modality image --image-pricing request --completion-image-price 0.01 --base-url https://api.example.com/v1 --bearer-token "$UPSTREAM_KEY" --upstream-model flux
polli my-models update <id> --description "Updated description"
polli my-models update <id> --paid-only            # only accept Paid Pollen; --no-paid-only reverts
polli my-models update <id> --required-safety privacy,secrets,sexual,violence,shield
polli my-models delete <id>

my-models manages owned community text, image, and transcription models. Any account can create private models; communityEndpointsAllowed: true is required only to publish them. API keys require account:keys. Use account:usage for narrow read-only usage and polli quests; use both permissions when a client needs both read-only account state and admin operations. Quest claiming is dashboard-only; polli quests is read-only and account-aware.

Register an image my-model

polli my-models test --modality image --base-url https://api.example.com/v1 --bearer-token "$UPSTREAM_KEY" --model image-v1
polli my-models create --name my-image --title "My Image" --modality image --image-pricing request --completion-image-price 0.01 --input-modalities text,image --base-url https://api.example.com/v1 --bearer-token "$UPSTREAM_KEY" --upstream-model image-v1

Test before creating. The probe reports the pricing mode it detected and the input modalities it found, including whether the endpoint accepts image edits; pass those back as --input-modalities text,image to advertise edit support. polli my-models list shows them in the inputs column.

Two billing modes: --image-pricing request charges --completion-image-price per generated image, while --image-pricing tokens bills returned token usage per 1M through --prompt-text-price, --prompt-image-price, and --completion-image-price.

Prices only apply to --visibility public models. A private model is owner-only and always free, so every price flag above is stored as 0 until you publish — and making a published model private clears its prices again.

--modality is fixed at creation — update cannot change it.

Manage agents

polli agents list
polli agents get <id>
polli agents create --config agent.json --name my-agent --title "My Agent"
polli agents create --config code-agent.json
polli agents update <id> --config agent.json
polli agents sync <id>
polli agents delete <id>

Prompt-agent config contains systemPrompt, baseModel, and optional mcpServers; create also requires --name and --title. Code-agent config contains type: "code_agent" and a public GitHub repository with agent.ts at its root; its model ID, title, and description come from GitHub. Use server IDs from the MCP catalog. Updates are partial: send only the fields to change; the rest keep their values. sync deploys the latest GitHub revision of a code agent.

Creating an agent also creates its callable model listing. Managed agents are text-only and free, with no fallbacks or per-user RPM. Deleting the agent also deletes its model listing. See Publish an Agent.

Manage API keys

polli keys list                                                    # list all keys on the account
polli keys info                                                    # details about the CURRENTLY AUTHENTICATED key only (takes no id)
polli keys create --name "my-bot" --type secret --budget 1000 --permissions profile usage   # scoped key
polli keys create --name "my-app" --type publishable --redirect-uri https://app.example/callback --earnings
polli keys create --name "server" --models black-forest-labs/flux.1-schnell tongyi-mai/z-image-turbo  # only these two models
polli keys update <id> --models text black-forest-labs/flux.1-schnell  # every text model plus FLUX.1 Schnell
polli keys revoke <id>                                             # id comes from `keys list --json`

--models takes categories (text, image, video, audio, 3d, embedding, realtime) and model IDs from polli models. A category includes models added later; a model ID allows only that model. --permissions <perms...> scopes what the new key can do on the account (e.g. profile usage lets it call polli --key <new> usage). Without --permissions, new scoped keys can generate media but cannot read account state — polli --key <new> usage will 403. Include keys to let the new key create, list, and revoke keys itself. Existing keys with account:keys can manage my-models where that invite-only feature is enabled, but still need account:usage for read-only account state. Publishable app keys default developer earnings off; pass --earnings to enable them. To inspect a specific key other than the current one, use polli keys list --json | jq '.[] | select(.id == "<id>")'. keys info is intentionally scoped to the caller's own key.

Connect a coding harness

Polli defaults to openai/gpt-6-sol; --model <id> overrides it. Bloom is key-only and keeps its own model selection.

polli harness --help                # supported harnesses
polli harness bloom on              # create a dedicated key for Bloom CLI
polli harness dsh on                # login if needed, mint key "polli-harness-dsh", write provider + default model
polli harness dsh on --model moonshotai/kimi-k2.6 # use the model ID from `polli models`
polli harness dsh on --no-mcp       # configure the provider and skill without MCP tools
polli harness dsh off               # restore the config backed up before "on"
polli harness hermes on             # login if needed, mint key "polli-harness-hermes", add provider + Polli skill
polli harness hermes on --model deepseek/deepseek-v4-flash # use the model ID from `polli models`
polli harness hermes off            # restore the config backed up before "on"
polli harness opencode on           # enable the Pollinations OpenCode plugin
polli harness opencode off          # remove the plugin setup and stored key
polli harness pi on                 # login if needed, mint key "polli-harness-pi", configure Pi with Pollinations
polli harness pi on --model moonshotai/kimi-k2.6 # use the model ID from `polli models`
polli harness pi off                # restore the Pi config backed up before "on"
polli harness openclaw on           # login if needed, mint key "polli-harness-openclaw", add provider + Polli skill
polli harness openclaw off          # remove the Pollinations provider, key, and skill
polli harness tgpt on               # use tgpt's Pollinations provider with a dedicated key
polli harness tgpt off              # restore tgpt's previous configuration

Each adapter checks that its harness can be launched before login, key creation, or configuration. DSH's official launch uses npx, so its adapter checks for npx; Bloom, Hermes Agent, OpenCode, OpenClaw, Pi, and tgpt require their installed commands.

Bloom already uses Pollinations and only needs a dedicated key in $BLOOM_HOME/.env (default ~/.bloom/.env). tgpt's existing Pollinations provider is selected in ~/.config/tgpt/config.conf with a dedicated key and model. The DSH adapter globally configures the Pollinations provider, hosted Pollinations MCP, and this skill under $DSH_HOME (default ~/.dsh). OpenCode enables the existing Pollinations plugin and stores its dedicated key in the plugin config. OpenClaw adds a pollinations provider to ~/.openclaw/openclaw.json, stores a dedicated key in env.vars, and installs this skill under ~/.openclaw/skills/polli/. Pi writes ~/.pi/agent/models.json, auth.json, and settings.json, and installs this skill under ~/.pi/agent/skills/polli/. Guide: polli docs section "Coding Harnesses".

Read API docs

polli docs                          # full llm.txt reference
polli docs /v1/chat/completions     # filter to one endpoint
polli docs --open                   # open in browser

Output contract

Default (human mode): varies by command — most emit key: value pairs or tab-separated tables with a header row. Exceptions: gen text prints the full response to stdout; gen transcribe prints the transcript as plain text; gen chat runs an interactive REPL. Status/progress messages go to stderr, so pipes stay clean.
--json: every command emits machine-parseable JSON to stdout; all human messages go to stderr. Always prefer --json when piping into jq or parsing — it's the only shape with a stable contract.
Exit codes: 0 on success, non-zero on auth failure, rate limit, network error, or invalid args. Error messages go to stderr.

Agent operating rules

Run polli auth status (or polli whoami) first if you don't know whether the user is logged in. Fail fast with a clear "run polli auth login" message if not.
Prefer --json whenever you'll parse the output. Never grep human-formatted tables.
Don't hardcode model IDs. Fetch the live list with polli models --type <type>. Model availability changes.
Before picking a model for production use, check polli models --stats. Rule of thumb for "healthy": err% ≤ 5, avg latency in a reasonable range for the modality (standard text <5s, image <10s, video <60s), and requests high enough to be statistically meaningful (ignore rows with <10 requests — noise). Filter by capability first, then optimize by health — e.g. for a reasoning task, narrow to models where reasoning: true (via polli models --type text --json), then cross-reference against --stats output. The healthiest model overall may not support the capability you need. Reasoning models are inherently slower — expect 5–50s, not <5s; when picking among them, prioritize low err% and request count over raw latency, and compare latency only within the reasoning-capable subset.
Always pass --output <path> for gen image, gen audio, gen video — otherwise the file lands in the current directory with a default name.
For stdin-as-context on gen text, pipe the context and pass the question as the positional argument: cat file | polli gen text "question about the file".
For exact flag lists, run polli <cmd> --help or polli gen <cmd> --help. This skill's recipes cover the common path; the CLI's own help is always the source of truth.
Use polli docs [endpoint] over guessing API shapes. It prints the canonical llm.txt reference from the live API.

Common pitfalls

Forgetting --output on binary generators (image/audio/video) — the file goes to a default path, which may not be what the user wants.
Using polli gen text --json expecting OpenAI chat-completions shape — the CLI's --json wraps its own structure. Use polli docs /v1/chat/completions to see the raw API shape if you need it.
Running commands without auth — polli auth status / polli whoami tells you who you're logged in as and your balance in one call.
gen text streams to a TTY, buffers when piped. The default now auto-detects — a human at the terminal sees tokens tick in, a pipe/redirect gets the full response once. Force either mode with --stream or --no-stream. For scripts and chains like polli gen text … | polli gen audio …, you don't need to do anything; buffering happens automatically.
Translating a polli workflow into a browser app. gen.pollinations.ai requires a bearer token for generation requests, so a plain client-side fetch with no auth returns 401 unless it is served from cache. Mint a scoped key with polli keys create and proxy via your own backend.
Backgrounded polli gen can fail silently — no output file, empty log, no error (a safety rejection is an explicit 400). Run in the foreground; if backgrounded, check the --output file exists and retry once in the foreground before calling it failed.
Content-safety 400s aren't only about violence. Body-focused action phrasing can trip a sexual-content category on some edit models. Rephrase the benign intent neutrally (e.g. sport framing) and retry with a new seed.

Agent Skills: polli — Pollinations CLI

Install this agent skill to your local

Skill Files