research-collector

research-collector is a skill for Claude Code from Kit4Some/Oh-my-ClaudeClaw. It costs 88 tokens per session (3,023 once invoked), scanned A, original, MIT.

A web-research automation pipeline that searches from several angles, collects pages, stores structured findings in persistent memory, and produces a report.

In plain words
What is it for?
Use it for competitor analysis, market research, technology trends, people research, news collection, and other web investigations.
Why use it?
It avoids repeating known research and keeps new information organized around what is already known.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Part of the openclaw-cc plugin — 22 skills, 4 agents, 5 MCP servers shipped together

Good fit Use it for competitor analysis, market research, technology trends, people research, news collection, and other web investigations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kit4some/oh-my-claudeclaw/research-collector
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.

Any agent
npx skills add Kit4Some/Oh-my-ClaudeClaw --skill research-collector
Clone the repo
git clone --depth 1 https://github.com/Kit4Some/Oh-my-ClaudeClaw

Made for: Claude Code.

Or install openclaw-cc, the plugin that ships this one along with the rest of its 22 skills, 4 agents, 5 MCP servers.

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-collector

README.md
[![agentmods](https://agentmods.dev/badge/skills/kit4some/oh-my-claudeclaw/research-collector/github.svg)](https://agentmods.dev/skills/kit4some/oh-my-claudeclaw/research-collector)
Your own site
<a href="https://agentmods.dev/skills/kit4some/oh-my-claudeclaw/research-collector"><img src="https://agentmods.dev/badge/skills/kit4some/oh-my-claudeclaw/research-collector/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.

agentmods 80×15 button for research-collector

Your own site · 80×15
<a href="https://agentmods.dev/skills/kit4some/oh-my-claudeclaw/research-collector"><img src="https://agentmods.dev/badge/skills/kit4some/oh-my-claudeclaw/research-collector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,023 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00088 $0.03023
Opus 5 $0.00044 $0.01511
Sonnet 5 $0.00018 $0.00605
Haiku 4.5 $0.00009 $0.00302

Measured 11d ago against content hash 3220653fd3f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

research-collector 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/format-report.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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-collector/SKILL.md · 274 lines

How it starts

The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Collector — 리서치 & 정보 수집 자동화 파이프라인

역할

사용자의 리서치 요청을 분석하여, 웹 검색과 페이지 수집을 통해 정보를 모으고, 구조화하여 메모리에 영구 저장한 뒤, 표준 보고서로 보고한다. 작업 시작 전 memory_search로 기존 관련 지식을 확인하고, 기존 정보와의 delta를 중심으로 수집한다.

사용 MCP 도구

도구 용도
memory_search 기존 관련 메모리 조회 (작업 시작 시 필수)
memory_store 수집 결과 영구 저장
web_search 다각도 검색 쿼리 실행
web_fetch 유망 URL 상세 페이지 수집

리서치 파이프라인 5단계

Step 1 — 요청 분석

사용자 요청에서 3가지를 판별한다:

항목 질문 판별 기준
주제 무엇에 대한 리서치인가? 핵심 키워드 1~3개 추출
정보 유형 어떤 종류의 정보가 필요한가? 아래 유형 분류표 참조
깊이 얼마나 깊이 조사할 것인가? quick / standard / deep

정보 유형 분류:

유형 트리거 표현 리서치 전략
경쟁사 분석 "경쟁사", "competitor", "비교" → 경쟁사 분석 전략
기술 동향 "동향", "trend", "기술 스택", "최신" → 기술 동향 전략
인물 조사 이름+소속, "누구", "프로필" → 인물 조사 전략
시장 조사 "시장", "market", "규모", "성장률" → 시장 조사 전략
일반 조사 위 어디에도 해당 안 됨 → 기술 동향 전략 변형

깊이 판정:

깊이 쿼리 수 web_fetch 수 소요 시간
quick 3개 1~2개 1분 이내
standard 5개 3~5개 2~3분
deep 8개 5~10개 5분+

기본값: standard. 사용자가 "간단히", "빠르게" → quick. "자세히", "심층", "깊이" → deep.

Step 2 — 검색 전략

깊이에 따라 3~8개의 검색 쿼리를 생성한다.

쿼리 생성 규칙:

  1. 이중 언어: 모든 주제에 대해 한국어 쿼리 + 영어 쿼리를 쌍으로 생성
  2. 다각도: 동일 주제를 다른 관점에서 검색 (뉴스, 기술, 비즈니스, 오피니언)
  3. 날짜 키워드: 최신성이 중요하면 "2026", "latest", "recent", "최근" 포함
  4. 구체화: 첫 검색 결과를 보고 후속 쿼리를 좁혀감

쿼리 구조 템플릿:

쿼리 1 (한국어 일반):  "{주제} {정보유형} 최신"
쿼리 2 (영어 일반):    "{topic} {info_type} 2026 latest"
쿼리 3 (한국어 구체):  "{주제} {세부키워드} {날짜범위}"
쿼리 4 (영어 구체):    "{topic} {specific_keyword} {date_range}"
쿼리 5+ (확장):       결과 기반 후속 쿼리 (deep 모드 시)

Step 3 — 정보 수집

실행 순서:

  1. web_search로 각 쿼리 실행
  2. 검색 결과에서 유망 URL 선별 (제목·snippet 기반)
  3. 선별된 URL을 web_fetch로 상세 수집
  4. 각 소스에서 핵심 데이터 포인트 추출

소스 우선순위 (높은 순):

순위 소스 유형 예시
1 공식 발표·보도자료 기업 블로그, PR Newswire
2 주요 테크 미디어 TechCrunch, The Verge, ZDNet Korea
3 전문 분석 리포트 Gartner, CB Insights, Statista
4 커뮤니티·포럼 Hacker News, Reddit, GeekNews
5 개인 블로그·SNS Medium, Twitter/X, 개인 블로그

Read the full file on GitHub · 274 lines

Files

What ships with it

2 files 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.

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. 11d ago First seen · 274 lines · 88 tokens per session scan A 3220653fd3f1

Subscribe to this mod's changes

research-collector is a skill published in the GitHub repository Kit4Some/Oh-my-ClaudeClaw (4 stars, last pushed 5mo ago), licensed MIT. It adds 88 tokens to every session and 3,023 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 2026-08-31.

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