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 Adelie-Squad/solosquad --skill market-researchgit clone --depth 1 https://github.com/Adelie-Squad/solosquadWrote 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/adelie-squad/solosquad/market-research)<a href="https://agentmods.dev/skills/adelie-squad/solosquad/market-research"><img src="https://agentmods.dev/badge/skills/adelie-squad/solosquad/market-research/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/adelie-squad/solosquad/market-research"><img src="https://agentmods.dev/badge/skills/adelie-squad/solosquad/market-research.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 | $0.00077 | $0.00671 |
| Opus 5 | $0.00039 | $0.00336 |
| Sonnet 5 | $0.00015 | $0.00134 |
| Haiku 4.5 | $0.00008 | $0.00067 |
Grade A, and why
market-research 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.
What it actually says
Market Research — Multi-agent Desk Research + Report
목적: 타깃 시장·경쟁사를 병렬 desk research 로 조사하고, 모든 주장에 인용(evidence_ref) 을 달아 groundedness 를 검증한 뒤 리포트를 산출. 1인 초기엔 인터뷰 대신 desk research·시장 신호로 보완하고 "추후 인터뷰 계획"을 명시(§3.6). 합성 위치(v1.3.5): market-research 서브워크플로(design/researcher + product/business-strategy).
절차
- 질문 분해 — 타깃 시장(TAM/SAM 신호)·경쟁사·대체재·가격·진입장벽으로 조사 질문을 나눈다.
- 병렬 조사 — 각 질문을 독립적으로 조사(멀티에이전트 가능). 출처 URL/문서를 기록.
- 인용 검증(groundedness) — 각 주장에
evidence_ref(출처) 부착. 출처 없는 주장은 추측으로 표시하거나 제거. 상충 출처는 병기. - 리포트 산출 —
<org>/reports/market-research-<slug>-<date>.md작성(아래 구조). - 요약 반환 — PRD §시장 에 들어갈 요약 + 리포트 경로(evidence_ref) 반환.
리포트 구조
# Market Research — <topic> (<date>)
## 요약 (3–5줄)
## 시장 규모 / 신호 — 각 항목 [evidence_ref]
## 경쟁사 / 대체재 — 표: 이름·포지셔닝·강점·약점 [evidence_ref]
## 기회 / 차별화 가설
## 미해결 질문 (open_questions[]) — 추후 인터뷰/검증 계획
## 출처
Anti-Sycophancy
낙관 편향 금지 — 시장 규모·수요는 출처로만 진술하고, 출처가 약하면 신뢰도를 낮춰 표기한다. 최소 2개 시나리오(낙관/보수)를 비교한다.
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 · 51 lines · 77 tokens per session scan A 5c3a2f86480f
market-research is a skill published in the GitHub repository Adelie-Squad/solosquad (19 stars, last pushed 20d ago), licensed MIT. It adds 77 tokens to every session and 671 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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