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 skills/imgompanda/fireauto/fireauto-research-guidenpx skills add imgompanda/fireauto --skill fireauto-research-guidegit clone --depth 1 https://github.com/imgompanda/fireautoWrote 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/imgompanda/fireauto/fireauto-research-guide)<a href="https://agentmods.dev/skills/imgompanda/fireauto/fireauto-research-guide"><img src="https://agentmods.dev/badge/skills/imgompanda/fireauto/fireauto-research-guide.svg" alt="Measured on agentmods" 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 | $0.00082 | $0.00932 |
| Opus 5 | $0.00041 | $0.00466 |
| Sonnet 5 | $0.00016 | $0.00186 |
| Haiku 4.5 | $0.00008 | $0.00093 |
Grade A, and why
fireauto-research-guide 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 4d 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.
What it actually says
Reddit 기반 시장 조사
Reddit은 B2B/B2C SaaS 시장 조사에 가장 풍부한 무료 데이터 소스 중 하나이다. 사용자들이 익명으로 솔직한 의견을 공유하기 때문에 설문조사보다 진솔한 인사이트를 얻을 수 있다.
핵심 워크플로우
1. 데이터 수집
Reddit 공개 JSON/RSS 엔드포인트를 활용하여 인증 없이 데이터를 수집한다.
주요 엔드포인트:
- 서브레딧 검색:
reddit.com/r/{sub}/search.json?q={query}&restrict_sr=1&sort=relevance&t=month - 최신글:
reddit.com/r/{sub}/new.json?limit=25 - 댓글:
reddit.com/comments/{post_id}.json
Rate limiting: 요청 간 최소 2초 간격, 세션당 최대 100 요청.
2. 서브레딧 선정
좋은 서브레딧 기준: 최소 10K subscribers, 일 평균 5개 이상 포스트, 질문 비율 30% 이상.
3. 리드 스코어링 (1-10점)
| 차원 | 배점 | 기준 |
|---|---|---|
| 참여도 | 2.5점 | 댓글 >= 10 (+1), upvotes >= 20 (+1), 둘 다 높으면 (+0.5) |
| 콘텐츠 깊이 | 2.5점 | 500자+ (+1.5), 구체적 요구사항 (+1) |
| 긴급성 | 2.5점 | urgency 키워드 수에 비례 |
| 도움요청 | 2.5점 | 질문형 (+1), "recommend" (+1), 예산 언급 (+0.5) |
4. 4-Tier 분류
- hot_lead (8-10): 구체적 요구사항 + 예산 + 긴급성
- warm_lead (5-7): 문제 인식 + 솔루션 탐색 중
- cold_lead (3-4): 관련 대화에 참여하나 구매 의향 불명확
- not_a_lead (1-2): 관련 없음 또는 false positive
5. False Positive 필터 (12 패턴)
반드시 not_a_lead로 거부:
- 불만토로/좌절 공유 (가장 흔한 false positive)
- 경쟁자가 직접 만드는 사람
- 어필리에이트/파트너십 제안
- 일반 토론 스타터 ("How did you get your first 100 users?")
- 이미 솔루션 찾은 사람
- 학생/취미 프로젝트
- 구인/구직 포스트
- 자기홍보/스팸
- AMA/인터뷰
- 뉴스/트렌드 공유
- 밈/유머
- 플랫폼 메타 토론
6. Pain Point 분류
| 카테고리 | 키워드 예시 |
|---|---|
| Cost | "expensive", "budget", "pricing" |
| Time | "takes forever", "slow", "deadline" |
| Complexity | "complicated", "learning curve" |
| Regulation | "GDPR", "compliance", "OSHA" |
| Scale | "growing", "can't handle", "enterprise" |
결과물
- CSV: post_url, subreddit, author, title, lead_score, urgency_level, pain_points, existing_solutions 등 13컬럼
- 마크다운 리포트: 요약 통계, Top 10 리드, Pain Point 분포, 경쟁사 언급
커맨드
/fireauto-research 실행으로 전체 파이프라인을 시작한다.
추가 리소스
상세 방법론은 references/methodology.md 참조.
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.
- 4d ago First seen · 84 lines · 82 tokens per session scan A b2f0116c1636
fireauto-research-guide is a skill published in the GitHub repository imgompanda/fireauto (140 stars, last pushed 4mo ago), licensed MIT. It adds 82 tokens to every session and 932 once invoked, about $0.0004 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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Resolve PR review feedback. Fetches unresolved threads, triages, fixes, replies and resolves via GraphQL. Use when asked to address review comments.
flow-next-tracker-sync
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