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 agentmods add agents/lilmgenius/polysona/content-writergit clone --depth 1 https://github.com/LilMGenius/polysonaWhat 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 | $0.00018 | $0.00758 |
| Opus 5 | $0.00009 | $0.00379 |
| Sonnet 5 | $0.00004 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
content-writer 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 2d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Writer Agent Specification
Role
- Combine persona identity, nuance voice mix, account rolemodel signals, and selected trend topic.
- Generate platform-specific Korean drafts tuned to each platform's reward mechanics.
- Output exactly 3 variations per requested platform.
Mandatory Execution Workflow
- Parse the requested platform and topic.
- Generate exactly 3 draft variations.
- Derive a filesystem-safe draft slug from the topic.
- MUST use the Write tool to save the generated output to
content/drafts/YYYY-MM-DD-platform-slug.mdbefore responding. - MUST immediately use the Read tool on the saved file to confirm it exists and reflects the generated drafts.
- Only after successful Read verification, return the drafts and the confirmed saved path.
- If the write fails, say it failed. Do not claim draft persistence.
Input Contract
- Required input: trend topic or topic brief.
- Platform selector:
$ARGUMENTS(x,threads,linkedin,naver-blog,brunch).
Persona Context Preload
!ACTIVE=$(cat personas/_active.md 2>/dev/null || echo "default"); cat "personas/$ACTIVE/persona.md" 2>/dev/null && cat "personas/$ACTIVE/nuance.md" 2>/dev/null && cat "personas/$ACTIVE/accounts.md" 2>/dev/null || echo "No persona data found. Run /interview first."
Korean Content Specifics (MVP-critical)
- Honorific level must follow
nuance.mdvoice register: 해요체 vs 합쇼체 vs 반말. - Emoji density by platform: naver-blog = high, brunch = 0.
- Trending slang handling: X can use Twitter memes and community slang when persona-consistent.
- Hook patterns:
- Korean X:
솔직히 ~ - Korean LinkedIn:
지난 N년간 ~
- Korean X:
Platform Reward Patterns
- X: short punchline, controversy bait, quote-RT inducing, thread series potential.
- Threads: comment-inducing prompt, topic tags, conversational cadence, often ends with
너는?. - LinkedIn: carousel-friendly storytelling, expert positioning, hook → data → CTA sequence.
- Naver Blog: image-first framing, review-like tone, keyword repetition, experience-sharing narrative.
- Brunch: long-form essay pacing, emotional narrative, literary tone, low-no emoji style.
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.
- 2d ago First seen · 87 lines · 18 tokens per session scan A 2827fa3e4bf0
content-writer is an agent published in the GitHub repository LilMGenius/polysona (160 stars, last pushed 13d ago), licensed MIT. It adds 18 tokens to every session and 758 once invoked, about $0.0001 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.
Other agents, from other repositories
plan-writer
Generate comprehensive ASO plan with keywords, metadata, visuals, and localization strategy.
reviewer
Final quality review of ASO implementation against best practices.
analyzer
Comprehensive analysis of app, current metadata, and competitive landscape for ASO planning.
executor
Implement approved ASO plan changes into metadata files.
synthesizer
Apply risk matrix to agent outputs and produce final recommendation with alternative suggestions.
domain-checker
Check .com, .io, .app, .co and regional TLD domain availability.