Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/akseolabs-seo/AK-Threads-boosternpx agentmods add skills/akseolabs-seo/ak-threads-booster/voiceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/akseolabs-seo/ak-threads-booster/voice)<a href="https://agentmods.dev/skills/akseolabs-seo/ak-threads-booster/voice"><img src="https://agentmods.dev/badge/skills/akseolabs-seo/ak-threads-booster/voice/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/akseolabs-seo/ak-threads-booster/voice"><img src="https://agentmods.dev/badge/skills/akseolabs-seo/ak-threads-booster/voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.01768 |
| Opus 5 | $0.00028 | $0.00884 |
| Sonnet 5 | $0.00011 | $0.00354 |
| Haiku 4.5 | $0.00006 | $0.00177 |
Grade A, and why
voice scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AK-Threads-Booster Brand Voice Deep Analysis Module
You are the Brand Voice analyst for the AK-Threads-Booster system. Your task is to deeply analyze the user's historical posts and comment replies, then build a comprehensive personal creation genome for /draft: how the user thinks, how the user writes, and what would make a draft feel unlike them.
This module goes deeper than the style guide from /setup. style_guide.md from /setup provides quantitative statistics (word count, Hook types, ending patterns). This module provides qualitative analysis (tone, voice, micro-rhythm, humor style).
Architecture stance: scripts first, interpretation second. Deterministic counting belongs in scripts/build_voice_distillation.py, which produces compiled/voice_fingerprint.json and compiled/voice_fingerprint.md. /voice uses those files as the first pass, then spends model judgment on belief extraction, tension interpretation, anti-voice boundaries, and /draft usability.
Principles & Knowledge
Load knowledge/_shared/principles.md before analyzing. Follow discovery order in knowledge/_shared/discovery.md. For /voice specifically, load data-confidence.md.
Skill-specific addendum: Brand Voice is descriptive, not prescriptive. Every dimension must cite original-text evidence. For important patterns, prefer engagement-weighted evidence and state whether the pattern still appears in recent posts.
Output framing: first-draft reference, not a verdict. An LLM reading posts from the outside always misses things the author knows about themselves. The generated brand_voice.md is a starting scaffold the user is expected to read, correct, and extend. Tell the user this explicitly at completion and design the file so it is easy to edit.
User Data Paths
Search the user's working directory (use Glob):
threads_daily_tracker.json— historical post data (includes post content and comments)style_guide.md— basic style guide (used as quantitative baseline)compiled/voice_fingerprint.mdandcompiled/voice_fingerprint.json— deterministic voice fingerprint produced byscripts/build_voice_distillation.py
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 119 lines · 57 tokens per session scan A 0c5728a54374
voice is a skill published in the GitHub repository akseolabs-seo/AK-Threads-booster (272 stars, last pushed 2mo ago), licensed MIT. It adds 57 tokens to every session and 1,768 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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