Borrowing it
Nothing to install: this file belongs to hwandam77/Hybrid-Gemini-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hwandam77/Hybrid-Gemini-mcp/main/.claude/skills/hybrid-gemini/SKILL.mdgit clone --depth 1 https://github.com/hwandam77/Hybrid-Gemini-mcpWrote 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/hwandam77/hybrid-gemini-mcp/hybrid-gemini)<a href="https://agentmods.dev/skills/hwandam77/hybrid-gemini-mcp/hybrid-gemini"><img src="https://agentmods.dev/badge/skills/hwandam77/hybrid-gemini-mcp/hybrid-gemini/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/hwandam77/hybrid-gemini-mcp/hybrid-gemini"><img src="https://agentmods.dev/badge/skills/hwandam77/hybrid-gemini-mcp/hybrid-gemini.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 | $0.00080 | $0.01885 |
| Opus 5 | $0.00040 | $0.00942 |
| Sonnet 5 | $0.00016 | $0.00377 |
| Haiku 4.5 | $0.00008 | $0.00188 |
Grade A, and why
hybrid-gemini 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 12d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hybrid-Gemini-mcp
Gemini AI 기반 통합 MCP 서버 (46개 도구)
기능 요약
| 기능 | 도구 수 | MCP 서버 | 용도 |
|---|---|---|---|
| Persona | 6 | hybrid-gemini-mcp | AI 전문가 상담 |
| Memory | 11 | hybrid-gemini-mcp | mcp-memory-service 연동 (시맨틱 검색, 지식 그래프, 품질 스코어링) |
| Conversation | 6 | hybrid-gemini-mcp | 대화 세션 관리 |
| Workflow | 4 | hybrid-gemini-mcp | 도구 체이닝 |
| Sandbox | 6 | hybrid-gemini-mcp | 코드 실행 |
| File | 5 | hybrid-gemini-mcp | 파일 조작 |
| SSH | 3 | hybrid-gemini-mcp | 원격 명령 |
| MCP | 3 | hybrid-gemini-mcp | MCP 서버 호출 |
| Cache | 4 | hybrid-gemini-mcp | 응답 캐싱 |
| Streaming | 2 | hybrid-gemini-mcp | 스트리밍 응답 |
⚠️ RAG 도구 (11개) Deprecated: mcp-memory-service의 memory_search, memory_graph, memory_ingest로 대체됨
사용 시나리오
시나리오 1: 코드 리뷰 자동화
1. file_read → 코드 로드
2. ask_reviewer → 품질 리뷰
3. ask_security → 보안 분석
4. memory_store → 결과 저장 (시맨틱 검색 가능)
시나리오 2: 디버깅 세션
1. memory_search → 이전 세션 검색 (시맨틱)
2. sandbox_python → 코드 테스트
3. ask_debugger → 에러 분석
4. memory_store → 세션 저장
시나리오 3: 지식 기반 개발
1. memory_search → 관련 지식 시맨틱 검색
2. memory_graph → 지식 그래프 탐색
3. ask_architect → 설계 상담
4. workflow_execute → 자동화 실행
빠른 시작
페르소나
mcp__hybrid-gemini-mcp__ask_architect(question="설계 질문")
mcp__hybrid-gemini-mcp__ask_debugger(issue="에러", context="로그")
mcp__hybrid-gemini-mcp__ask_reviewer(code="...", focus="security")
메모리 (mcp-memory-service)
# 저장 (시맨틱 검색 가능)
mcp__hybrid-gemini-mcp__memory_store(
content="프로젝트 아키텍처: FastAPI + React",
metadata={"tags": ["project", "architecture"]}
)
# 시맨틱 검색
mcp__hybrid-gemini-mcp__memory_search(query="FastAPI 관련 설정", mode="semantic")
# 지식 그래프
mcp__hybrid-gemini-mcp__memory_graph(action="connected", hash="abc123", max_hops=2)
# 문서 인제스트
mcp__hybrid-gemini-mcp__memory_ingest(directory_path="/docs", tags=["documentation"])
샌드박스
mcp__hybrid-gemini-mcp__sandbox_python(code="print(1+1)")
mcp__hybrid-gemini-mcp__sandbox_javascript(code="console.log([1,2,3])")
mcp__hybrid-gemini-mcp__sandbox_eval(expression="Math.sqrt(16)")
What ships with it
8 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.
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.
- 12d ago First seen · 196 lines · 80 tokens per session scan A 27c7f660d27f
hybrid-gemini is a skill published in the GitHub repository hwandam77/Hybrid-Gemini-mcp (0 stars, last pushed 7mo ago), licensed MIT. It adds 80 tokens to every session and 1,885 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.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.