Speak Summary

Turn written text into audio someone will actually want to listen to.

This skill is deliberately a terminal step in a chain. Another skill (or you) produces the text; this one makes it listenable. It pairs naturally with roundup, daily-prep, meeting-minutes, or any summarisation work.

Everything runs locally on CPU. No text is sent to a cloud speech service, which matters when the content is confidential, and it means the skill works in a headless cloud agent or CI container just as well as on a laptop.

Prerequisites

The synthesis engine is Kyutai pocket-tts, a small neural TTS model designed to run on CPUs.

The bundled script installs it automatically into a cached virtualenv on first use, so usually you need do nothing. To install it explicitly:

pip install pocket-tts          # any platform
brew install pocket-tts         # macOS, if preferred

pocket-tts requires Python >=3.10 and <3.15. The script searches for a compatible interpreter rather than assuming python3 is one — worth knowing if you are on a very new Python, where installation would otherwise fail.

You also need an encoder. ffmpeg is strongly preferred (brew install ffmpeg or apt-get install -y ffmpeg); on macOS the script falls back to the built-in afconvert and emits .m4a instead of .mp3.

The first run downloads the model (~1GB) from Hugging Face. After that it is fully offline and synthesises roughly 6x faster than real-time.

The important step: rewrite for the ear

Do not feed written text straight into the synthesiser. Prose that reads well on screen is tiring to listen to. Rewriting it first is what separates a useful audio digest from an unlistenable one.

Produce a spoken script that:

• Opens with orientation. What this is, what it covers, roughly how long it runs.
• Replaces bullets with connective prose. "First… The bigger one is… Finally…" — a listener has no visual structure to lean on, so carry it in the language.
• Expands abbreviations on first use. "PR" becomes "pull request", "CI" becomes "continuous integration". Acronyms that read fine are noise when spoken.
• Speaks dates and numbers naturally. "the twentieth of August", not "2026-08-20". "About three thousand", not "2,847".
• Never reads URLs aloud. Say "linked in the written version" instead.
• Uses short sentences. Split anything past roughly 25 words.
• Signposts transitions. "Turning to the product side…", "Two things need your attention…".
• Ends with the actions. Recap what the listener should do, since that is what they need to retain and they cannot scroll back.
• Drops anything purely visual. Tables, code blocks, and diagrams should be summarised in a sentence or omitted, never read out.

Write this spoken script to its own .txt file. Keep the original written version with its links intact — the audio is a companion to it, not a replacement. The user will want to click through later.

Synthesise

./scripts/tts.sh <input.txt> <output.mp3> [voice.safetensors]

The script strips any residual markdown, splits the text on sentence boundaries into ~600 character chunks (quality degrades on long single inputs), synthesises each chunk, and concatenates the result into a mono MP3 at 96kbps — small enough to sync to a phone, good enough for speech.

Environment overrides:

| Variable | Purpose | |---|---| | SPEAK_TTS_BIN | Path to a specific pocket-tts binary; skips all auto-detection. | | SPEAK_TTS_HOME | Where to create/find the cached virtualenv. Default ~/.cache/speak-summary/venv. |

Voices

The default English voice is alba. To use a different one, pocket-tts supports voice cloning from a short clean audio sample:

pocket-tts export-voice --help

Pass the resulting .safetensors file as the third argument to the script.

Only clone a voice you have the rights to use. Do not clone a real person's voice — colleague, customer, or public figure — without their explicit consent.

Output

• Default to ~/Music/Briefings/ unless the user says otherwise; it is easy to point a phone or podcast app at.
• Name files <subject>-<YYYY-MM-DD>.mp3.
• Report the path, duration, and size.
• Offer to play it: afplay <path> on macOS, ffplay -nodisp -autoexit <path> elsewhere.

Length guidance

Aim for 4–6 minutes for a routine digest, which is roughly 600–900 spoken words at a natural pace. If the source would run past about 10 minutes, say so and offer either a tighter edit or a split into multiple files — attention drops off sharply beyond that for informational audio.

Chaining onto other skills

The natural pattern is gather → summarise → speak:

• roundup → speak-summary — a spoken version of the status briefing.
• daily-prep → speak-summary — tomorrow's schedule, listened to tonight.
• meeting-minutes → speak-summary — catch up on a meeting you missed.

When invoked as part of a chain, do not re-summarise. The upstream skill owns what to say; this skill owns how it sounds. Take its output, rewrite it for the ear, and synthesise.

To run unattended (a briefing waiting before breakfast), schedule the upstream skill with a workflow and have it finish by calling this one.

Troubleshooting

Audio cuts off mid-sentence. A chunk exceeded the model's comfortable length. Shorten the sentences in the spoken script.

Words mispronounced. Spell them phonetically in the input — "Kubernetes" as "koo-ber-net-eez". This is a normal part of preparing a spoken script.

First run is slow. That is the one-off model download. Later runs start in about a second.

pocket-tts not found after install. The virtualenv may be stale, or your python3 may be outside the supported 3.10–3.14 range. Delete ~/.cache/speak-summary/venv and re-run, or point SPEAK_TTS_BIN at a known binary.