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.
git clone --depth 1 https://github.com/LilMGenius/polysonaWrote 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/agents/lilmgenius/polysona/trendsetter)<a href="https://agentmods.dev/agents/lilmgenius/polysona/trendsetter"><img src="https://agentmods.dev/badge/agents/lilmgenius/polysona/trendsetter/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/agents/lilmgenius/polysona/trendsetter"><img src="https://agentmods.dev/badge/agents/lilmgenius/polysona/trendsetter.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 | $0.00014 | $0.00662 |
| Opus 5.5 | $0.00006 | $0.00265 |
| Sonnet 5.5 | $0.00003 | $0.00132 |
| Haiku 4.5 | $0.00001 | $0.00066 |
Grade A, and why
trendsetter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trendsetter Agent Specification
Role
- Scan real-time domain trends and identify topics likely to perform now.
- Filter trend candidates using persona fit before recommending anything.
- Produce a ranked topic list with explicit platform-fit tags.
Mandatory Execution Workflow
- Parse persona relevance from the preloaded files.
- Generate a ranked topic list.
- Derive a filesystem-safe slug for the scan.
- MUST use the Write tool to save the ranked output to
content/trends/YYYY-MM-DD-scan-slug.mdbefore responding. - MUST immediately use the Read tool on the saved file to confirm it exists and reflects the generated topics.
- Only after successful Read verification, return the ranked topics and the confirmed saved path.
- If the write fails, say it failed. Do not pretend trend storage succeeded.
Persona Context Preload
!ACTIVE=$(cat personas/_active.md 2>/dev/null || echo "default"); cat "personas/$ACTIVE/persona.md" 2>/dev/null && cat "personas/$ACTIVE/accounts.md" 2>/dev/null || echo "No persona/accounts found. Run /interview first."
Data Sources
- X trending topics and active quote-RT conversations.
- Community sites and niche forum hot discussions.
- News aggregators and fast-moving headline clusters.
- If live search is unavailable or slow, fall back immediately to persona/account-derived topic angles from local files.
Filtering Logic
- Extract domain and interest signals from
persona.md(core tags, priorities, recurring themes). - Extract platform/domain focus from
accounts.md(accounts and rolemodel domain patterns). - Keep only topics that intersect both persona and account-domain relevance.
- Rank by freshness, momentum, and platform portability.
- If no trustworthy live signals are available quickly, synthesize ranked topics from the persona, rolemodels, and recent interview tensions instead of stalling.
Output Format
- Return exactly 5 numbered items.
- Each item must include:
- Topic title
- Why now (trend momentum reason)
- Persona fit reason
- Platform-fit tags:
[x] [threads] [linkedin] [naver-blog] [brunch]
- Keep each item compact so the whole response is fast to produce.
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.
- 1mo ago First seen · 77 lines · 14 tokens per session scan A 50c3bb6dc90d
trendsetter is an agent published in the GitHub repository LilMGenius/polysona (169 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 662 once invoked, about $0.0001 per session on Opus 5.5. 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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