Documentation Index
Fetch the complete documentation index at: https://docs.coconut.dev/llms.txt
Use this file to discover all available pages before exploring further.
What you get
A recurring loop that mines recent activity across your workspace — meeting transcripts, internal chat threads, code and design reviews, commit messages and pull request descriptions, decision documents, planning notes, knowledge contributions — for things your team’s distinctive voices (founders, executives, technical leads) actually said in their own words. It synthesizes those signals into a single knowledge file, grouped by speaker and tagged by topic, that downstream content skills can quote from directly. Marketing and content channels default to bland company-voice when the people with distinctive points of view aren’t in the loop on every post. Without this skill, “POV voice” content is the marketer guessing at the speaker’s perspective — polished but inauthentic, and it tends to underperform with exactly the audiences who would have responded to the real thing.What’s inside
- Skill:
pov-voice-loop(rename if you’d like) - Job: Run weekly, or on whatever cadence matches your content schedule
- Input list:
voices.md— the named people you want to track, with their role - Output:
pov-voice-snippets.md— single file, grouped by speaker, tagged by topic, refreshed every run
Set it up
Paste the prompt below into your skill builder. It’s standalone — it doesn’t depend on any specific platform, only on having avoices.md you can edit and access to the activity sources you’d like the skill to mine.
I want a skill calledpov-voice-loopthat mines recent activity in the workspace for what a named set of people — founders, executives, technical leads, anyone with a distinctive point of view — actually said in their own words, and synthesizes those signals into a single knowledge file that downstream content skills can quote from. Refresh on a weekly cadence. Role. You are a careful editor who values directness over polish. Your job is to surface what these people actually said — not to paraphrase, not to clean it up, not to translate it into “company voice.” If a quote is rough or partial, that’s better than a smoother version that loses the original phrasing. Read first.For each tracked voice, look for things they actually said this past week, across the sources you have access to.
- The list of voices to track at
voices.mdin the knowledge base (one named person per line, with their role).- The existing
pov-voice-snippets.mdfile if it exists — so you know what’s already on record.- Any role, team, or memory notes that describe how each person tends to communicate.
What earns inclusion. A quote belongs in the file when:
- Meeting transcripts where they spoke.
- Internal chat threads.
- Code review and design review comments.
- Commit messages and pull request descriptions.
- Decision documents and planning notes.
- Knowledge base contributions.
Skip housekeeping (“looks good, ship it”), tone-only comments, and anything that already reads like marketing copy. Synthesize into
- The phrasing is distinctive — specific, opinionated, or vivid, not generic.
- It expresses a point of view or makes a call, not just describes a fact.
- It’s tied to a real moment (a meeting, a thread, a decision).
pov-voice-snippets.md. Group by speaker first, then by topic within each speaker. For each snippet, capture:Refresh strategy. Rewrite the file on every run, but carry forward older snippets that are still on-topic and still represent the speaker’s view. Drop snippets that have been superseded by something the same person said more recently on the same topic. The file should grow with the person, not pile up over time. Quality over volume. No more than about 6 snippets per speaker per run. If a speaker had a quiet week, say so explicitly rather than padding with weak quotes. Run summary. At the end of the run, output a short summary: which voices yielded snippets this week, which were quiet, and any sources you couldn’t access (so the operator can fix the gap for next week). Hard bans — do not produce.
- The quote, verbatim or near-verbatim.
- The speaker.
- One or two topic tags.
- The source and date.
- A one-line note on context — what was being decided or discussed.
Once we’ve agreed on the skill, install it and set up a weekly job.
- Paraphrased “what they meant” — quote the real words or skip the snippet.
- Snippets without a named source and date.
- Generic statements any executive at any company might say.
- “Voice” reconstructed from style alone, with no specific quote behind it.
What happens on each run
The skill readsvoices.md, scans the activity sources it has access to for each named person, filters for the distinctive moments where they actually said something, and rewrites pov-voice-snippets.md with the freshest representative quotes per speaker per topic. Older quotes that are still on-topic carry forward. Superseded ones drop off. Quiet weeks show up as quiet rather than padded.
What the output looks like
Keep going
Downstream content skills should read frompov-voice-snippets.md as a signal source — drafting POV-voiced posts that quote what was actually said, rather than paraphrasing it through a company-voice filter. The further your content drifts from these quotes, the more it starts to sound like every other company.