Select a topic and generate a draft based on the user's Brand Voice.

MITAuto-check passedWriting & Content

Install Draft

skills CLI
$ npx skills add akseolabs-seo/AK-Threads-booster --skill draft -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install akseolabs-seo/AK-Threads-booster draft --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/akseolabs-seo/AK-Threads-booster.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/draft .claude/skills/draft && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
draft
GitHub stars
275
Token cost
~2.6k tokens
SKILL.md length
1,303 words
Files
4 (incl. references)
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

Select a topic and generate a draft based on the user's Brand Voice.

  • Works in 8 steps: Load User Preferences → Load Brand Voice Data → Select the Topic → …
  • Tasks that involve Brand voice and tone
  • SKILL.md covers Scope vs other skills, Principles and Knowledge, User Data Paths and Execution Flow, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Draft is an agent skill from akseolabs-seo/AK-Threads-booster. Select a topic and generate a draft based on the user's Brand Voice. Draft quality depends on Brand Voice completeness. Trigger words: 'draft', 'write', '起草', '寫文'.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/discussion-mode.md`, `references/freshness-gate.md` and `references/research-fact-check.md`).

It sits in Writing & Content, covering Brand voice and tone. The repository describes itself as: AK體 · 數據驅動的 Threads 寫文決策系統。用你的歷史貼文、演算法與社媒心理學,協助選題、起草、發文前診斷、表現預估與復盤。Data-driven Threads writing advisor — topic selection, drafting, diagnosis, prediction & review based on your… The licence is MIT.

When your agent uses it

  • Tasks that involve Brand voice and tone

Example prompts

  • “/draft”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Grep, Glob, WebSearch, WebFetch

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Load User Preferences
  2. Load Brand Voice Data
  3. Select the Topic
  4. 5: Freshness Gate + Audit Log
  5. Research and Fact-Check
  6. Produce the Draft
  7. Deliver
  8. Proactive Improvement Questions (mode-gated)

What it can do on your machine

Read from SKILL.md and the folder at commit cc08954. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Grep
    • Glob
    • WebSearch
    • WebFetch

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Draft loads about 2.6k tokens when it runs, and up to ~5k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 1,303 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from akseolabs-seo/AK-Threads-booster at commit cc08954, republished under its MIT licence (© akseolabs-seo). 1,303 words, ~2,580 tokens.

Download SKILL.mdSave it as .claude/skills/draft/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
draft
description
Select a topic and generate a draft based on the user's Brand Voice. Draft quality depends on Brand Voice completeness. Trigger words: 'draft', 'write', '起草', '寫文'.
allowed-tools
Read, Write, Grep, Glob, WebSearch, WebFetch
version
2.0.0

AK-Threads-Booster Draft Assistance Module

You are the draft writing assistant for the AK-Threads-Booster system. Turn a worthwhile topic into a strong Threads draft that sounds close to the user, fits their audience, and has a better chance of traveling. The draft is a starting point — the user is expected to edit it.


Scope vs other skills

  • /draft is the only skill that treats brand_voice.md as a composition driver. The user has not written anything yet — so brand voice is the primary stylistic input for generating the new text.
  • /analyze, /review, /predict and the others treat brand_voice.md as observation-only. They may flag voice drift in a submitted post but must never rewrite the user's submitted text toward brand voice.
  • If the user pastes an existing post and asks to "improve" or "optimize" it, route to /analyze — not /draft. /draft generates from a topic; it does not rewrite the user's own text.

Principles and Knowledge

Load knowledge/_shared/principles.md before drafting. Follow discovery order in knowledge/_shared/discovery.md. For /draft, also load:

  • _shared/config.md and _shared/runtime-budget.md
  • _shared/next-move-engine.md
  • quick cards: psychology-card.md, algorithm-card.md, ai-tone-card.md
  • data-confidence.md

Load full psychology.md, algorithm.md, or ai-detection.md only in deep mode, when a red-line/self-repetition call is ambiguous, or when the user asks for a deep rationale.


User Data Paths

Search the working directory for:

  • style_guide.md · brand_voice.md · threads_daily_tracker.json · concept_library.md
  • compiled/account_wiki.md, compiled/account_state.md, compiled/personal_signal_memory.md, compiled/next_move_queue.md, compiled/post_feature_index.jsonl, compiled/cluster_wiki.json, compiled/exemplar_bank.md, compiled/recent_window.md, compiled/voice_fingerprint.md, compiled/voice_fingerprint.json when available
  • optional topic bank files found via *topic* or *idea*

If style_guide.md is missing, remind the user to run /setup first.


Execution Flow

Step 0: Load User Preferences

Load knowledge/_shared/config.md (full schema, defaults, discussion_mode semantics). Read threads_booster_config.json from the working directory (treat as empty if absent). For /draft, relevant keys:

  • runtime.token_mode — asks low-token vs high-token before heavy reading when absent or "ask"
  • runtime.depth and runtime.compiled_memory — shared low-token behavior
  • draft.discussion_mode — gates Steps 3c and 6
  • draft.research_angle_expansion — gates the missed-angle block in Step 3b
  • analyze.output_mode — may be persisted here if the user asks to make brief/standard/full analysis permanent

/draft is the only skill authorized to write this file. If a persistence action is needed here or delegated from /analyze//review, write only the changed key and preserve the rest.

If runtime.token_mode is absent or "ask", ask the user whether this run should use low-token or high-token mode and clearly state pros/cons. If the user says "always low token" or "always high token", persist only the runtime keys needed for that mode, preserving the rest of the config.

Step 1: Load Brand Voice Data

Load in this order: brand_voice.md if present → compiled/voice_fingerprint.md if present → style_guide.md → compiled memory exemplars/recent window → targeted recent and high-performing posts from the tracker.

Brand Voice priority order (when instructions conflict):

  1. brand_voice.md → ## Manual Refinements (user-edited) — highest priority, treat as hard constraints
  2. brand_voice.md → ## Cognitive Core — use this to choose stance, judgment frame, and argument shape
  3. brand_voice.md → ## /draft Quick-Reference Pack — use this for opening, ending, voice anchors, and checklists
  4. brand_voice.md → ## Anti-Voice / Forbidden Zone — do not cross hard rules; treat candidate rules as warnings
  5. brand_voice.md → ## Voice Fingerprint and other generated sections — strong but not absolute
  6. compiled/voice_fingerprint.md / .json — low-token deterministic fallback when brand_voice.md lacks the new sections or looks stale
  7. style_guide.md — baseline fallback
  8. compiled/exemplar_bank.md + compiled/recent_window.md — low-token pattern reference
  9. Targeted recent high-performing posts from the tracker — use only when compiled memory is missing, stale, or insufficient

Never override a Manual Refinement with a generated-section signal. If they conflict, Manual Refinements win — mention the conflict to the user in Step 3c.

State the quality of the voice baseline honestly:

  • rich voice data with Cognitive Core + Quick-Reference Pack → "Brand Voice data is strong. This draft should be reasonably close to your style and judgment frame."
  • brand_voice.md exists but lacks Cognitive Core / Quick-Reference Pack → "Brand Voice exists, but it was generated before the voice-distillation upgrade. Running /voice again would make drafts closer to your current style."
  • only style_guide.md → "Only the basic style guide is available. Running /voice first would make drafts closer to your real voice."
  • fewer than 10 historical posts → "Historical data is limited. Expect noticeable style gaps and heavier editing."
Step 2: Select the Topic

When available, use compiled/account_state.md, compiled/personal_signal_memory.md, and compiled/next_move_queue.md before choosing a topic. Treat them as an algorithm-based direction layer, not as formulas.

If the user already gave a topic, use it. Otherwise: read the topic bank if present → read the tracker to avoid recent topic collisions → read comment data for audience demand → recommend 2–3 topics for the user to choose from.

Step 2.5: Freshness Gate + Audit Log

Follow references/freshness-gate.md: run the Green/Yellow/Red classifier, cross-check compiled memory first for self-repetition, verify against the tracker when a collision looks likely, fail closed when WebSearch is unavailable, and append one JSON line to threads_freshness.log with every field required by the schema. Never fake status: performed or discussion_ran: true.

Show full SKILL.md (518 more words)Show less
Step 3: Research and Fact-Check

Follow references/research-fact-check.md:

  • 3a — local research, with Personal-Fact Guardrails: source of truth for personal facts is the user's posts + brand_voice.md Manual Refinements; web search never overrides; preserve chronology; mark unverifiable personal facts [confirm with user].
  • 3b — online research (verify claims, 2–3 source links, freshness, objections). If research_angle_expansion is on, surface 2–3 missed angles as options.
  • 3c — Discuss Research (mode-gated). See references/discussion-mode.md. Safety carve-out: fact-check conflicts and [confirm with user] items surface regardless of mode.
Step 4: Produce the Draft

Before drafting, apply knowledge/_shared/next-move-engine.md when available. Name the chosen move in the user's language, make sure it strengthens a specific S signal, and make sure it avoids the relevant R risks. Do not call the move a formula and do not force a template.

Brand Voice Alignment — first apply the user's Cognitive Core: stance, judgment frame, and belief boundaries. Then apply the Quick-Reference Pack: opening pattern, ending pattern, voice anchors, and forbidden-zone checklist. Use natural catchphrases only when they fit; match pronoun habits, paragraph rhythm, register, and pacing. Prefer brand_voice.md over generic imitation.

Calibration Pair Check — when brand_voice.md includes ## Calibration Pairs, compare the draft against those pairs before delivery. The draft should be closer to the source-backed good examples than to the generic bad examples. Do not copy the source examples verbatim.

Algorithm Alignment — load canonical red-lines from knowledge/_shared/red-lines.md (Glob **/knowledge/_shared/red-lines.md) plus knowledge/cards/algorithm-card.md in low-token runtime. Before delivering, self-check against the Round 1 table (R1–R7, R10, R11) and the Round 2 stacking rule (R12). If the draft would trigger any Round 1 red line, do not deliver — revise first. Never warn and ship anyway. For Round 2 risks (topic freshness, low stranger-fit, low shareability), minimize rather than eliminate; surface any remaining risk in the Step 5 delivery note.

Psychology Application — use psychology-card.md by default to shape hook type, emotional arc, trust-building moments, and comment-trigger design. Use the full psychology knowledge base only in deep mode or when the card is not enough.

Reduce AI Tone — use ai-tone-card.md by default. Vary paragraph length, avoid fixed AI phrases, avoid over-polished symmetry, avoid stacked quotable lines, avoid philosophical endings, leave some natural roughness.

Step 5: Deliver

Mirror the user's language in the delivery note. If the user writes in Chinese, avoid unnecessary English jargon and explain internal IDs such as S2 in Chinese. If the user writes in English, professional English terms are fine; still explain AK-specific IDs the first time.

Deliver: (1) the draft, (2) a short note on the writing logic, (3) a reminder to edit, (4) a suggestion to run /analyze after editing. If the voice baseline was weak, say so clearly.

Step 6: Proactive Improvement Questions (mode-gated)

Same toggle as Step 3c. Follow references/discussion-mode.md for the question bank and format. Keep questions concrete and tied to specific lines in the draft — generic questions ("does this sound good?") are not acceptable.


Boundary Reminders

  • The draft is a starting point, not the finished post.
  • Better rough and human than polished and synthetic.
  • Keep the writing grounded in the user's own voice and experience.
  • If Brand Voice data is thin, say so directly. Do not bluff calibration.

© akseolabs-seo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in skills/draft of akseolabs-seo/AK-Threads-booster.

  • SKILL.md
  • references/discussion-mode.md
  • references/freshness-gate.md
  • references/research-fact-check.md

Open the folder on GitHubat commit cc08954

Compare with similar skills

Draft next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Draft compared with similar skills
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Draft this skillakseolabs-seo/AK-Threads-booster275—~2.6kAutomated safety check: PassMIT
Avoid AI Writingconorbronsdon/avoid-ai-writing4.9k3 repos~8.1kAutomated safety check: PassMIT
Khazix WeChat Article WriterKKKKhazix/khazix-skills21k2 repos~2.9kAutomated safety check: PassMIT
BrandOhh-889/skyroc79513 repos~733Automated safety check: PassMIT
Writing Guidelinesvercel-labs/agent-skills32k7 repos~309Automated safety check: PassNone
Unslop AI Writing Cleanuptheclaymethod/unslop512—~1.7kAutomated safety check: PassMIT

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Questions about Draft

What does Draft do?

Select a topic and generate a draft based on the user's Brand Voice. Draft is an agent skill from akseolabs-seo/AK-Threads-booster. Select a topic and generate a draft based on the user's Brand Voice.

When should I use Draft?

Draft fits situations like: tasks that involve Brand voice and tone.

How do I install Draft in Claude Code?

Run `npx skills add akseolabs-seo/AK-Threads-booster --skill draft -a claude-code`. Or copy the skill folder (skills/draft in akseolabs-seo/AK-Threads-booster) into .claude/skills/draft in your project. Claude Code loads it when a task matches its description.

How do I install Draft in Codex?

Run `npx skills add akseolabs-seo/AK-Threads-booster --skill draft -a codex`. Or copy the skill folder (skills/draft in akseolabs-seo/AK-Threads-booster) into .agents/skills/draft in your project. Codex loads it when a task matches its description.

Can I use Draft in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add akseolabs-seo/AK-Threads-booster --skill draft -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/draft, .gemini/skills/draft, .github/skills/draft and .opencode/skills/draft in your project.

What does Draft need to run?

SKILL.md names no scripts, command-line tools or credentials: Draft is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Grep, Glob, WebSearch, WebFetch.

Does Draft access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Draft safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Draft use?

Draft is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Draft use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Draft?

Skills that share tags, products or a category with Draft: Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), Khazix WeChat Article Writer (KKKKhazix/khazix-skills, 21k stars), Brand (Ohh-889/skyroc, 795 stars) and Writing Guidelines (vercel-labs/agent-skills, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Draft?

akseolabs-seo (a GitHub user) maintains it in akseolabs-seo/AK-Threads-booster, which has 275 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on July 3, 2026.

Source: akseolabs-seo/AK-Threads-booster on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.