Forward Deployed Engineer delivery contract for AWS engagements, build-first artifacts, grounded cost estimates, Well-Architected review, evolution roadmap
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OSINT investigation — discover, track, and report on people, companies, and technologies
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Conduct open-source intelligence gathering on specific targets — people, companies, technologies, or markets. Discover publicly available information, track changes over time, assess source reliability, and produce structured intelligence reports.
This is NOT the awareness loop (which monitors Genesis's own systems). This is outward-facing investigation — finding information about external entities.
Define the target clearly:
Build 10-20 search queries tailored to target type:
Person:
"[name]" [company] — basic association"[name]" site:linkedin.com — public LinkedIn profile"[name]" [industry] interview OR podcast OR keynote"[name]" [company] announcement OR appointed OR promoted"[name]" github OR gitlab — technical contributionsCompany:
"[company]" funding OR "series A" OR "series B" OR acquisition"[company]" hiring OR careers OR "we're hiring"site:crunchbase.com "[company]" — Crunchbase profilesite:stackshare.io "[company]" OR site:builtwith.com "[company]" — tech stack"[company]" review OR glassdoor — employee sentiment"[company]" revenue OR valuation OR growthTechnology:
"[technology]" benchmark OR comparison OR vs"[technology]" production OR deployment OR "in production""[technology]" github stars OR contributors OR releases"[technology]" adoption OR migration OR "switched to"For each query:
Source quality heuristics:
For each data point, extract entities and relationships:
Entity types: Person, Organization, Product, Event, Financial, Technology, Location
Relationship types: works_at, founded, invested_in, competes_with, partnered_with, launched, acquired, uses_technology, located_in, reports_to
Store as structured records:
entity:
name: <canonical name>
type: <entity type>
attributes:
title: <if person>
industry: <if company>
founded: <if company>
headcount: <if known>
sources:
- url: <source URL>
reliability: <very_high | high | medium_high | medium | low>
date_accessed: <YYYY-MM-DD>
first_seen: <YYYY-MM-DD>
confidence: high | medium | low
If this is a follow-up cycle on a previously investigated target:
Produce a structured intelligence report:
# OSINT Report: [Target Name]
**Date:** YYYY-MM-DD
**Depth:** surface | deep | exhaustive
**Sources consulted:** N
## Summary
<3-5 sentence overview of key findings>
## Entity Profile
<structured profile data>
## Key Findings
1. <finding with source>
2. <finding with source>
## Changes Since Last Report (if applicable)
- [CRITICAL] <change>
- [IMPORTANT] <change>
## Relationships
<entity → relationship → entity map>
## Source Quality
| Source | Reliability | Data Points |
|--------|------------|-------------|
## Confidence Assessment
<overall confidence in findings, gaps identified>
## Recommended Follow-Up
- <what to investigate next>
- <what to monitor>
Before trusting any data point, check:
If 3+ checks fail, downgrade confidence to "low."
site:linkedin.com via search engines onlyinvestigation_id: <OSINT-YYYY-MM-DD-NNN>
target: <name>
target_type: <person | company | technology | market | competitor>
date: <YYYY-MM-DD>
depth: <surface | deep | exhaustive>
sources_consulted: <count>
entities_extracted: <count>
key_findings:
- finding: <description>
confidence: high | medium | low
sources:
- <URL>
significance: critical | important | minor
changes_detected:
- change: <description>
significance: critical | important | minor
recommended_actions:
- <next step>
monitoring_schedule: <none | weekly | daily>
src/genesis/skills/research/SKILL.md — General research methodologysrc/genesis/memory/ — MemoryStore for persistencedocs/reference/gemini-routing.md — For video content during investigation아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Forward Deployed Engineer delivery contract for AWS engagements, build-first artifacts, grounded cost estimates, Well-Architected review, evolution roadmap
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Canonical guide to Genesis browser automation - layers (Camoufox, Chromium, the user's Chrome over CDP, TinyFish, desktop), per-tool timeouts, safety gates, verify-after-act, what a click checks (scroll, hit test, covered targets), overlays, iframes, tabs, and failure diagnosis
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Update Claude Code (the CC CLI / "clog code") to a new version, or bump the pinned CC version. Use when the user asks to update Claude Code, bump the CC pin, evaluate a new CC release, or says "clog code update". Routes to the canonical, standardized process in docs/reference/cc-compatibility.md — do NOT re-derive the update mechanism by grepping every time. Do NOT use for general "what changed in CC" trivia with no intent to update.
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This skill should be used when a session's job is to DRIVE OPEN PRs TO MERGE rather than to write new code — "close out the open PRs", "review and fix the open PRs", "what's blocking our PRs", "which PRs are mergeable". It owns the In Review column: it reads each PR's gate status, verifies and fixes review findings on PRs OTHER sessions built, replies in-thread, and stops at the merge gate for the user's per-PR approval. Do NOT load it for building a feature and opening its PR — that is a build session (`genesis-development`).
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Code understanding tool selection. Use when exploring architecture, finding definitions, tracing call chains, assessing blast radius of changes, or debugging code paths in the Genesis codebase.
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End-to-end content creation and publishing. Takes a topic (or generates one), drafts in the user's voice, gets approval via Telegram, and publishes to Medium via browser automation. Invoke with "publish a post about X", "write and publish to Medium", "content-publish", or when an ego-dispatched session needs to create and distribute content.
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