research-pack

research-pack is a skill for Claude Code, Codex from kohj1018/agentic-dev-harness. It costs 62 tokens per session (866 once invoked), scanned A, original, MIT.

A research skill that uses official documents, primary sources, and academic papers to create a source-linked research note with confidence labels. It separates verified facts from conclusions drawn from those facts.

In plain words
What is it for?
Use it to investigate a focused question, break it into smaller questions, gather sources, label their reliability, and save a structured research note without changing code or planning documents.
Why use it?
It makes external research easier to check and keeps evidence separate from interpretation before planning or implementation decisions are made.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/kohj1018/agentic-dev-harness/research-pack
Any agent
npx skills add kohj1018/agentic-dev-harness --skill research-pack
Clone the repo
git clone --depth 1 https://github.com/kohj1018/agentic-dev-harness

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for research-pack

README.md
[![agentmods](https://agentmods.dev/badge/skills/kohj1018/agentic-dev-harness/research-pack.svg)](https://agentmods.dev/skills/kohj1018/agentic-dev-harness/research-pack)
Your own site
<a href="https://agentmods.dev/skills/kohj1018/agentic-dev-harness/research-pack"><img src="https://agentmods.dev/badge/skills/kohj1018/agentic-dev-harness/research-pack.svg" alt="Measured on agentmods" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 866 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00062 $0.00866
Opus 5 $0.00031 $0.00433
Sonnet 5 $0.00012 $0.00173
Haiku 4.5 $0.00006 $0.00087

Measured 5d ago against content hash e828e68b2c2d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

research-pack 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 5d 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.

.claude/skills/research-pack/SKILL.md · 61 lines

What it actually says

이 skill은 리서치 + 노트 작성 전용이다. 코드·workitem·charter 문서를 수정하지 않는다 (노트 파일 1개만 작성).

메인 세션에서 실행한다(context: fork/agent: 미지정 — discover-product 패턴). 무거운 웹 조사는 researcher agent에 Agent 위임해 메인 컨텍스트 오염을 막는다. researcher는 report-only이고, 노트 Write는 본 skill이 한다.

Codex: 본 skill은 wrapper 미보유(자연어 호출) — Codex에서는 "Follow .claude/skills/research-pack/SKILL.md"로 호출한다(목록 SSOT = README, ADR-010#amend-3·#amend-4).

너의 역할은 입력 질문을 1차/공식 출처 기준으로 조사해 신뢰도 라벨이 붙은 리서치 노트를 작성하는 것이다.

입력:

  • $ARGUMENTS에 리서치 질문/주제가 들어온다 (예: "Stripe Payment Intents 최신 idempotency 정책", "회고 SaaS 경쟁 제품 onboarding 패턴").

반드시 할 일:

  1. 질문을 검증 가능한 하위 질문 2~4개로 쪼갠다.
  2. 조사: 무거운 웹 조사는 researcher agent에 Agent 위임(노이즈 격리 — 결론 1~2K 토큰만 반환). 가벼운 단건 확인은 본 skill의 WebSearch/WebFetch로 직접. 공식문서·1차 자료·논문 우선, 2차 블로그는 보조.
  3. 각 발견에 출처 URL + 발행일 + [공식]/[1차]/[2차] 신뢰도 라벨.
  4. "사실"과 "제품/구현 시사점(추론)"을 분리한다.

마지막 단계 — 리서치 노트 작성:

  • 경로: docs/10-charter/insights/<YYYY-MM-DD>-<slug>.md (slug는 주제 kebab-case).
  • 양식:
# Research: <주제>

- 작성일: <YYYY-MM-DD>
- 질문: <원 질문>
- type: research | external-research

## 발견 (신뢰도 라벨)
- [공식] <발견> — <URL> (<발행일>)
- [1차] ...
- [2차] ...

## 사실 ↔ 추론 분리
- 사실: ...
- 제품/구현 시사점(추론): ...

## DISCOVERY 연결 제안
- Evidence Log(§14) 추가 후보: source=<URL>, type=external-research, finding=<...>, confidence=<상/중/하>
- 관련 가정/기회: <A-N 또는 신규>

마지막 출력 (메인에 텍스트로):

  • 노트 경로
  • 핵심 발견 3개 + 신뢰도 라벨
  • DISCOVERY Evidence Log 반영 권장 (자동 반영 X — /discover-product --update가 회수)

가드:

  • workitem / charter / 코드 일체 수정 금지 (insights/ 노트 1개만 Write).
  • 추측을 사실처럼 쓰지 않는다. 출처 없는 주장 금지.

Context 정책 (ADR-019)

반드시 먼저 읽을 파일최소 충분. 추가 자료는 발화 시 인용 — 사전 fork-load 금지.

Changes

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.

  1. 5d ago First seen · 61 lines · 62 tokens per session scan A e828e68b2c2d

Subscribe to this mod's changes

research-pack is a skill published in the GitHub repository kohj1018/agentic-dev-harness (2 stars, last pushed 8d ago), licensed MIT. It adds 62 tokens to every session and 866 once invoked, about $0.0003 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 2026-08-31.

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