narrated-poem
Skill2 starsChanged 24 days agoMITView on GitHub
Turn a picture into a spoken poem — a vision model describes the image, an LLM writes a short poem from the description, and a text-to-speech model narrates it. Use when the user wants a poem, narration, or spoken-word piece inspired by an image file.
- Reads credentials
In this repository10 other files it gives its agents.
- alt-text-writerSkill
- character-spritesSkill
- jingle-makerSkill
- og-card-makerSkill
- photo-restylerSkill
- poster-generatorSkill
- pr-describerSkill
- ui-mockupSkill
- video-teaserSkill
- visual-judgeSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- could be automatic: a setting could enforce it
- Distinctive: line 18
Never print the key.
- Very specific: line 31
Add --env-file .env only when the key is not already exported.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Narrated poem
Runs the bundled nanoodle workflow workflows/narrated-poem.noodle-graph.json against the
NanoGPT API: an image input (Picture) feeds a vision model that describes it, an LLM turns
the description into a four-line poem, and a TTS model speaks it (Narration). Requires
Node.js 22.23.4+, 24.22.1+, or 26.12.1+ and the nanoodle npm package (npx nanoodle fetches it).
API key
The run needs a NanoGPT API key. Prefer NANOGPT_API_KEY already in the environment.
Otherwise pass --env-file <path-to-.env> (this CLI: --env-file overrides ambient env).
Never print the key.
Run
From this skill's directory (or prefix paths if running from elsewhere). @path attaches a
local file:
npx nanoodle run workflows/narrated-poem.noodle-graph.json \
--input "Picture=@/path/to/picture.jpg" \
--out ./poem-outAdd --env-file .env only when the key is not already exported. Add --json for a
structured result (paths, costUsd, remainingBalance).
Optional overrides:
--input "Poet=<custom poet instructions, e.g. write a limerick instead>"
--set "n4.voice=am_michael" # pick a Kokoro voice (af_bella, am_adam, bf_emma, …)
--set "n2.q=<different question to ask about the image>"Inspect the interface anytime with:
npx nanoodle inspect workflows/narrated-poem.noodle-graph.jsonInputs
| Key | Required | What to pass |
Picture | yes | @<path> to the user's image file (jpg/png/webp) |
Poet | no | Custom instructions for the poem-writing LLM (its system prompt) |
Poet is the node name shown in the editor. It replaces that node's system prompt.
Outputs
- Media is saved under
--outasNarration.<ext>— extension follows the audio MIME (oftenmp3orwav). Use the path the CLI prints on theNarration:line; do not hard-code the extension. - With
--json, the path is inoutputs.Narration.
Cost
Each run costs about $0.01 in NanoGPT credit (vision + LLM are fractions of a cent;
Kokoro-82m speech is ~$0.002 per poem). Runs spend real credit — tell the user before
running repeatedly.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

