Writing style and tone
Skill social-media-skills/skills/skills/writing-style-and-tone
The writing-craft skill — style and tone as applied technique: rhythm, specificity, tone modulation, and the edit passes that make writing read as human. Use when someone's posts "sound like ChatGPT," a draft needs a style edit, they ask how to write differently per platform or moment without losing the brand voice, writing is grammatically perfect but exhausting, a manager wants em dashes banned or detector scores chased, or any AI-assisted draft needs its mandatory quality pass. Uses the STYLE framework. Reads voice-builder + brand-profile + the format skill first. Tells must be read as a cluster with judgment — no single marker proves AI, and detectors misflag real writers; the winning move is substance so owned the question never arises. Voice is identity; tone is register. The agent drafts; the HUMAN supplies lived specifics and final say; never invents anecdotes or staged typos. Distinct from voice-builder, hook-writer, the format skills, and content-research-and-sourcing.From its SKILL.md
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SKILL.md
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writing-style-and-tone
The writing craft — sound like someone, tune tone to the moment, yank the dead weight, let the rhythm breathe, and edit against the tells intelligently. The agent drafts and edits in the voice; the human supplies the lived specifics and the final call; WoopSocial publishes. (Craft skill — no tool file.)
The POV: the tells are symptoms — the disease is saying what anyone could say
2026 quantified the stakes: 52% of consumers say they disengage the moment they suspect copy is AI, only 13% say they completely trust AI, experienced AI users now detect machine text at near-perfect rates, and discovery systems treat predictable-pattern content as noise. So the tell taxonomy matters — the delve-class vocabulary (44% of PubMed's all-time "delve" appearances landed in 2023–24), "It's not X, it's Y," the forced rule-of-three, the rigid intro-point-point-conclusion shape, fluff sentences, relentless positivity — but the top-1% position holds two truths at once. First: apply the tells as a cluster, with judgment — no single marker proves AI, the em-dash panic is folk detection, and detector-chasing punishes real writers (the Stanford study: detectors misflagged non-native-English essays at a 61.3% average false-positive rate). Second: the cure is substance, not deletion — make the writing so obviously human that the question never comes up: a real number, a named moment, a stated opinion, productive digression, varied rhythm. Say what only you could say. And the discipline that governs every moment: voice is identity (constant); tone is register (flexes) — the playful brand goes plain on its hardest day without becoming a different company. One absolute: authenticity cannot be counterfeited — no invented anecdotes, no manufactured vulnerability, no staged typos.
Read these first
- voice-builder — the voice this craft inhabits (the constitution; this skill governs by it).
- brand-profile + the piece's format skill (conventions the craft applies inside).
The framework: STYLE
(Depth: references/the-style-framework.md.)
- S — Sound like someone: one only-you element per piece (number, moment, opinion); concrete over abstract; subjectivity as a feature.
- T — Tune tone to the moment: the tone map (celebration / education / sales / complaint / crisis) with voice fingerprints persisting; platform register shifts, identity doesn't (the cover-the-handle test).
- Y — Yank the dead weight: fluff sentences deleted whole; throat-clearing cut; verbs over adjectives; one idea per sentence; front-load.
- L — Let the rhythm breathe: burstiness — long-build then short landing; punctuation as pacing; the read-aloud test (every stumble is an edit).
- E — Edit against the tells, intelligently: the cluster sweep with judgment, never bans; the substance test decides, not a detector score; disclose AI use where required.
The reality (verify-quarterly)
The stakes: Bynder's 52% disengagement figure; Klaviyo's 13% complete-trust figure; near-perfect detection by
experienced AI users (Russell et al.); information-gain systems penalizing sameness. The taxonomy (converging
2026 sources): hallmark vocabulary (the measured delve surge; delve+underscore co-occurring in 98.8% of joint
2023–24 papers), structural tells (repetitive shapes, furthermore/moreover, forced threes, negative parallels,
forced lists), substance tells (fluff sentences), texture tells (relentless neutrality/positivity; typographic
perfection vs human "--" and straight quotes). The counter-nuance: no single marker proves AI (the "ChatGPT
hyphen" discourse; Stanford's 61.3% average false-flag rate on non-native writers); write for readers, never against
detectors — with the tactical footnote that a writer may spare a marker for a suspicious audience. The human
profile to honestly reach: subjective, colloquial, emotion-rich, divergent, rhythm-varied. Attribute all;
verify-quarterly. Full detail: references/writing-style-2026-reality.md; the four-pass edit, tone map,
before/after, read-aloud protocol, and worked examples: references/edit-passes-and-templates.md.
Honest scope (never violate)
- The agent drafts in the voice, runs the four passes, renders tone per the map, and flags where a real specific is needed — placeholders stay visibly unfilled until the human supplies lived material and signs off. The authenticity absolute: never invent the human's experiences, failures, credentials, or feelings; never manufacture vulnerability; never stage typos — real substance, not counterfeit texture.
- Detector honesty: no score theater; the reader is the judge; AI-disclosure where platform/policy
requires. Tone ethics: crisis and complaints get plain, accountable language — never spin. Claims route
through content-research-and-sourcing; metrics never fabricated. (Full scope:
references/scope-and-connections.md.)
Distinct from its siblings (route correctly)
writing-style-and-tone (this) = the applied prose craft + tone control · voice-builder = defines the voice (this inhabits it) · hook-writer / hooks-and-retention-deep-dive = the first line (this owns everything after) · text-post-and-microblog / caption / email skills = format conventions · copywriting/conversion skills = persuasion architecture (this is the prose layer under it) · content-research-and-sourcing = verifies the claims this styles · contrarian-and-opinion = the POV strategy this renders · every AI-drafting workflow = this is its mandatory edit layer.
Where this connects
Reads first: voice-builder + brand-profile + the format skill. Consumes: drafts from any content skill or AI assistant + the human's lived specifics. Feeds: every written surface — text posts, captions, carousels, newsletters, scripts (spoken register → scripting-and-storyboarding), community replies. Publishes via: the finished piece → scheduling-and-queue → WoopSocial. Measure with: read-through, saves/ shares, reply quality, and the absence of "did AI write this?" comments via analytics-and-reporting — never fabricated.
Definition of done
Prose that passes the substance test before any tell sweep: at least one only-us element per piece (a real number, named moment, or defensible opinion supplied by the human — never invented), dead weight yanked (no fluff sentences, no throat-clearing, verbs doing the work), rhythm varied and read aloud until stumble-free, tone rendered deliberately from the map (voice fingerprints constant; cleverness dialed to zero as stakes rise; the cover-the-handle test passed across platforms), and the tell cluster swept with judgment — no banned punctuation, no detector-score theater, AI use disclosed where required; the agent flagging placeholder slots rather than fabricating lived experience, the human filling and approving them, claims verified via content-research-and-sourcing, and the piece published via WoopSocial; no invented anecdotes, manufactured vulnerability, staged imperfection, or fabricated metrics; and correctly distinguished from voice-builder, hook-writer, the format skills, and content-research-and-sourcing.
What ships with it: 5 files
22.0 KB alongside SKILL.md
evals/
- evals.json8.5 KB