Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Freespirits/social-auto-engine --skill newsletter-voicegit clone --depth 1 https://github.com/Freespirits/social-auto-engineWrote 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/freespirits/social-auto-engine/newsletter-voice)<a href="https://agentmods.dev/skills/freespirits/social-auto-engine/newsletter-voice"><img src="https://agentmods.dev/badge/skills/freespirits/social-auto-engine/newsletter-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/freespirits/social-auto-engine/newsletter-voice"><img src="https://agentmods.dev/badge/skills/freespirits/social-auto-engine/newsletter-voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00143 | $0.01823 |
| Opus 5 | $0.00072 | $0.00911 |
| Sonnet 5 | $0.00029 | $0.00365 |
| Haiku 4.5 | $0.00014 | $0.00182 |
Grade A, and why
newsletter-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 11d 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.
This is a copy
100% identical to newsletter-voice — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Newsletter Voice
Prerequisites check
The moment this skill is triggered, check the project root for voice.md and about-me.md.
If either file is missing, tell the user:
Newsletter voice sits on top of your general voice profile. Run voice-builder first (upload the skill or say "build my voice"), then come back here once about-me.md and voice.md are in the project.
Then stop. Do not continue until both files exist.
If both files exist, read them fully, then go straight to Step 1.
Step 1. Check for samples
Ask the user in chat:
Do you have 2 to 3 past newsletter issues I can learn from?
Yes: paste them here (one per message or all at once) No: type "archetype" and I will build from a template tuned to your voice
Wait for response.
If the user pastes 2 or more newsletters, go to Step 2a. If the user types "archetype", go to Step 2b. If the user pastes 1 newsletter, ask for at least one more. If they only have one, offer: "One sample is not enough for pattern detection. Want me to switch to archetype mode and use your one newsletter as a reference point?"
Step 2a. Sample-based analysis
Read every newsletter fully. Look for patterns across issues, not one-off quirks. Extract:
Opening formula
- What the first 3 sentences do (specific result, cultural observation, claim, scene, question)
- Length of the opening section before the first structural break
- Credibility move (how the author establishes authority early)
- Value promise (what the reader is told they will get)
Section structure
- Problem or contrast setup
- Named framework or free prose
- Numbered steps, methods, or continuous argument
- Examples and evidence patterns
- Bonus or extension section
- Closing formula and signoff
Data philosophy
- Specific numbers per issue (count them)
- Source attribution style (linked, named, uncredited)
- Example-to-abstraction ratio
- Limitation or failure acknowledgements
Formatting
- Header usage (frequency, hierarchy)
- List usage (numbered, bulleted, arrows)
- Bold and italic usage
- Prompt, code block, or blockquote formatting
- Visual markers (arrows, checkmarks, emojis if any)
What ships with it
1 file 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.
- 11d ago First seen · 173 lines · 143 tokens per session scan A a12237574024
newsletter-voice is a skill published in the GitHub repository Freespirits/social-auto-engine (25 stars, last pushed 1mo ago), licensed MIT. It adds 143 tokens to every session and 1,823 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to newsletter-voice, differing in 0 lines, and is treated as a copy.
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