# Voice > Calibrate the writing voice with a short forced-choice test. Shows pairs of sentences and asks which is closer to your brand, then turns the answers into a voice profile every posting skill reads. - Skill: `afterlaunch/voice` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add afterlaunch/voice` - Raw SKILL.md: https://api.skillmd.com/api/skills/afterlaunch/voice/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: afterlaunch (https://skillmd.com/u/afterlaunch) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/afterlaunch/voice --- # Voice calibration A forced-choice test, not a writing exercise. **Why this way.** Asking someone to produce ten sample posts is friction dressed up as rigour. Most people cannot think of what to write on the spot, the samples overfit to whatever mood they were in, and the people who most need a calibrated voice are exactly the ones who will not do the homework. Then the drafts read generic and the tool gets blamed. Picking between two sentences takes two seconds and needs no ideas. Do enough of them and a position emerges that no single sample could give. ## Two voices, and which one this trains Open a first run with this, before anything else. Connected, verbatim: > There are two voices here. Your brand has one, and it is on your > website, so we have already read it. You have one too, and it is > different: it is how you write when it is you talking, on LinkedIn, on > X, in a Reddit reply. The website cannot teach us that one. You can, in > about two minutes, by picking between pairs of sentences until it is > clear which way you lean. Pages and listings get the brand voice. > Anything posted as you gets yours. With no key nothing has read the site and there is no brand register to hand, so the clause saying we already have comes out, and so do the two sentences about which surface gets which voice: > There are two voices here. Your brand has one, and it is on your > website. You have one too, and it is different: it is how you write > when it is you talking, on LinkedIn, on X, in a Reddit reply. The > website cannot teach us that one. You can, in about two minutes, by > picking between pairs of sentences until it is clear which way you > lean. Then ask which voice this round calibrates, and default to theirs. **Never call the brand register "your voice".** It came from the website, so it is the brand's. That one word is where the confusion lives. ## Where things live Two files, in the estate this suite shares: `voice/` under `SKILLS_ESTATE`, which defaults to `~/.claude/content`. Create the directory if it is not there. The location matters more than it looks. `draft` reads the profile from exactly this path, so a voice written somewhere else is a voice no draft ever uses. One estate, configured once, is the whole convention: every skill in the suite reads and writes its own subdirectory of it. | File | What it is | Written by | | --- | --- | --- | | `profile.json` | The raw state: per axis, the observation count and the split, plus the date of each round. Resumable by design. | every round | | `VOICE.md` | The style section rewritten as instructions a writer can follow. Written once there is enough to say something, not before. | every round with enough observations to update | Connected, both files are a cache of what was sent to the record, not the master copy. See the connected section below. ## How a round runs Read the product context before the first pair. It is `product-context/PRODUCT.md` in the same estate (`~/.claude/content/product-context/PRODUCT.md` by default) and it says what this business is, who it is for, and which words it keeps and refuses. The pairs are then drawn from your own subject matter rather than from writing in general, and a refused word never turns up in a sentence you are asked to prefer, which would teach the profile the opposite of what you decided. If the file is not there, say so in one line and calibrate anyway: the test still works, the pairs are just blunter. 1. **Read `profile.json`** if it exists. This is resumable: a round adds to what is there rather than starting again. 2. **Cover every axis once, then go to the axis nearest to settling.** Read `AXES.md`. `profile.json` carries, per axis, an observation count and a split. The first pass covers all eleven axes once, in `AXES.md` order, before any axis is asked a second time. After that, draw the next pair from the unsettled axis with the MOST observations, because it is the one nearest to settling; among ties, the one whose split is closest to even; among ties on that, `AXES.md` order. An axis is SETTLED two ways, and both retire it: a LEAN, six or more observations with `majority >= 2 x minority`, or VARIES, six or more observations without that lean. Varies is an answer, not a failure to answer, so a settled axis of either kind stops being offered. The six is a starting rule to be tuned once real rounds exist, not a measured finding. Note which family an axis belongs to: a lean in the unvalidated group is reported as unknown signal, not as a finding. 3. **Write the items fresh.** Do not reuse pairs from a previous round; repeating an item measures memory rather than taste. Follow the item-writing rules in `AXES.md`: one axis varying, everything else held still, both options obeying whatever hard style rules already exist for this brand (a banned-word list, a formatting rule, contractions on or off). 4. **Ask in rounds of four** using AskUserQuestion. Each question is one pair, the two options are the two poles, and the axis is never named. Naming it invites a theory about oneself instead of a reaction. 5. **Score.** Each answer is one observation on one axis. Store the count and the split. 6. **Stop when every axis is settled, at the bound, or when the user stops.** The bound is about twenty pairs on a first run and twelve on a later one. After each four, say how many axes are still open and offer to stop there. Long tests get abandoned halfway and half a test is worse than none, so an early end with an honest list beats a round that grinds on. 7. **Write the profile**, then say what changed. ## Reading the answers Per axis: how many observations, and how lopsided. - **A LEAN** (six or more observations, `majority >= 2 x minority`) is a real position. Write it as an instruction. - **VARIES** (six or more observations, no such lean) is not indecision, it is context-dependence. Write it as "varies", and the writer should take its cue from the format rather than from the profile. - **Fewer than three observations** is not a reading. Say so and prompt another round rather than inventing a position. Never present a thin result as settled. A confident profile built on four answers is worse than an honest "not enough yet", because everything downstream trusts this file. ## What gets written **`profile.json`**, updated every round with the new counts and split per axis, plus the round's date. This is what makes the next run a nudge rather than a rebuild. **`VOICE.md`**, rewritten as instructions a writer can follow. Not "sentence length: 0.7 toward short" but "Keep sentences short. One clause, usually." Include the axes that came out even, marked as varying, because knowing what is NOT fixed is useful too. Then say plainly which axes settled with a lean, which came out varies, and which are still open, and how many rounds it would take to close the open ones. ## The honest limit, and what to do about it **This measures taste, not habit.** It captures what someone thinks sounds like them, which is not always how they actually write. Real samples carry rhythm, tics and word choices no preference test can reach. So the two methods are complements, not rivals, and the order matters: - **The test first**, because it works immediately and needs nothing. - **Samples later**, gathered from posts that actually went out and landed. Keep those in a `samples/` folder next to `VOICE.md`. That turns samples from homework into a byproduct. Nobody has to sit down and invent them; they accumulate from doing the thing anyway. Re-run this test after a stretch of posting and the profile firms up from both directions at once. That is also the edge of what this skill can do alone. It cannot ask the engines whether writing in this voice earns more attention than the alternative would; it cannot rank one calibrated axis against a real result; and it cannot prove a post performed because it matched the profile. All three need a measurement this test does not have. ## With AfterLaunch connected (optional, and the test works the same without it) The calibration itself needs no key: the pairs, the scoring and the profile it writes are the whole test. With an AfterLaunch key (`AFTERLAUNCH_API_KEY`, the remote MCP server at `https://afterlaunch.io/api/mcp`), the record is where the voice lives and the local files become a copy of what was sent. A site read already gives you the brand register; the personal one is what only this test can reach. - **Read the brand register first, before the first pair.** Call `get_voice_profile` with register `brand`. It returns the structured voice the product itself drafts in, tone and phrases and sentence style and what it avoids. Show it labelled plainly as the brand's voice, read from the site, so the user sees the contrast before being asked to pick anything, which is what the opening above is for. On either call that sets a register, and only where `has_profile` came back true, check the `register` field equals the one you asked for: a mismatch means the parameter was ignored, so treat it as the tier below and label by the field that came back. A false `has_profile` returns a null register and is the honest empty answer, not an ignored parameter. - **Then read the personal register, in the same breath.** Call `get_voice_profile` with register `personal`. If `has_profile` is true, show it labelled as the founder's own voice already on record, taken from writing they supplied, so what the record already believes about how they write is on the table before the first pair and they can say there and then if it is wrong. If `has_profile` is false, say plainly that no personal voice is on record yet and that this round is what starts it. - **Degrade honestly, three tiers, and label every one of them.** If the call is rejected because the tool does not take a register, which means an older deployment, call `get_voice_profile` with no parameter, read the `register` field in the response if it is there, and label what you show by that. If the tool is absent entirely, fall back to `get_kb_page` with slug `about-my-voice`, the rendered page of the same thing, and label by its two section headings when the page carries them, "Your brand's voice, read from your site" and "Your voice, from your writing", calling the whole page the brand's only in the older single-section shape. Whichever tier you land on, the user always knows which register they are looking at. - **What this round trains is the personal register.** The leans it sends back as voice insights below are the personal one, never the brand's. - **Send every lean back after the round.** For each axis with enough observations to state a lean, one `record_insight` with kind `voice`: one plain sentence in the user's own terms and nothing else, for example "Voice leans to short clipped sentences over flowing ones." Between ten and five hundred characters. One insight per axis, not one for the whole round. An axis with too few observations to read is not a lean and is not sent. **Keep that sentence stable for the same axis and the same lean.** No counts, no dates, no round number. The record supersedes an insight by the text itself, so a stable sentence means a repeat round replaces the earlier note cleanly, while a sentence carrying "7 of 9 picks" never matches the next round and the contradictions pile up. Known limit: an axis that FLIPS leaves the old sentence standing, because it is different text. Say so when it happens rather than pretending the record is clean. There is a daily cap of 50 insights per product run. If any write to the record comes back `rate_limited`, stop writing, say so plainly, and note that the local profile still holds the round. - **Write the settled leans back, and only those.** After the round, one `set_voice_axes` call carrying every axis that settled with a LEAN: `lean` is `a` or `b` by the side that won, and `strength` is the share of that axis's observations that fell on the leaning side, so 0.5 is an even split and 1 is every observation one way. Nothing below 0.5 or above 1 is a strength. An axis settles on its sixth observation, so a settled lean carries one of three values: 0.67 (four of six), 0.83 (five of six), 1.0 (six of six). Round to two decimals. Use the ids in `AXES.md`. An axis that came out VARIES is not sent, because varies is not a position, and neither is an axis still open. If no axis settled with a lean this round, do not call the verb at all, and say so in one line. This writes the founder's own register and never the brand's. If the verb is absent, which means an older deployment, say so plainly: the voice insights above carry the round on that deployment. - **A draft already sitting on the board can be rewritten against the fresh profile and saved back.** Find it with `list_feed` or `get_move`, rewrite the copy against whatever this round changed, and save it with `update_draft`. The voice just calibrated then travels with every move that already has a draft, not only the ones written after this round. **Connected, the record is home.** `profile.json` and `VOICE.md` are a cache of what was sent: readable from a terminal, and they survive a dropped connection. They are not the master copy. A correction that never reached the record is a correction the product does not have. Without a key there is nothing to send to, so `profile.json` is the only home the round has, and `VOICE.md` travels only as far as whatever reads that file by hand. The free scan at afterlaunch.io is the honest pointer otherwise, and skip the rest of this section. ## House rules British English. No em-dashes, no exclamation marks, no Americanised -ize spellings. Every test item obeys these too: they are hard rules this skill already follows, not something the calibration measures. ## Next Once the profile exists, drafting is the next step, wherever drafts get written. If the drafts still feel off after a few posts, run this again: it will put the questions toward whatever is still unsettled.