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dictcli

개인 어휘 그래프 — 한↔영 크로스링귀얼 쿼리 확장 + 한국어 형태소 분석. expand로 한글 단어에서 영어 태그 후보를 찾고, stem으로 한국어 어간을 추출한다. knowledge_search의 3층 역할. '단어 확장', '태그 찾기', '한영 매핑', 'expand', 'stem', '형태소'.

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UpdatedApril 21, 2026 at 00:33

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junghan0611

junghan0611/agent-config

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Software DevelopersComputer and Mathematical Occupations15-1252L4

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name	dictcli
description	개인 어휘 그래프 — 한↔영 크로스링귀얼 쿼리 확장 + 한국어 형태소 분석. expand로 한글 단어에서 영어 태그 후보를 찾고, stem으로 한국어 어간을 추출한다. knowledge_search의 3층 역할. '단어 확장', '태그 찾기', '한영 매핑', 'expand', 'stem', '형태소'.

dictcli — Personal Vocabulary Graph (Layer 3)

Korean↔English triple graph. Expands Korean words to English Denote tags. Layer 3 of knowledge_search — cross-lingual query enrichment.

API

Binary bundled in skill directory. Must cd to {baseDir} (reads CWD/graph.edn).

Command	Usage	Output
expand	`cd {baseDir} && ./dictcli expand "보편" --json`	`["universal","universalism","particular","paideia"]`
graph	`cd {baseDir} && ./dictcli graph "보편"`	All triples for the word
stats	`cd {baseDir} && ./dictcli stats`	Graph statistics
validate	`cd {baseDir} && ./dictcli validate`	Invariant check

expand — Core Command

Traverses the graph: direct translation → opposite's translation → related word's translation.

cd {baseDir} && ./dictcli expand "기술" --json   # → ["art","technology","technique"]
cd {baseDir} && ./dictcli expand "도피" --json   # → ["escape","flight","avoidance","evasion"]

Empty array = word not in graph.edn. Fall back to original query.

knowledge_search Integration Pattern

1. User: "보편 학문 관련 노트"
2. expand "보편" → ["universal","universalism","paideia"...]
3. Search: "보편 학문 universal universalism paideia"

Agent autonomously: extract concept words → expand → enrich query → knowledge_search.

stem — Korean Morphological Analysis

JVM-only (Kiwi JNI — not in native binary). Called via dictcli repo's run.sh stem. Agents rarely call directly — andenken batch-indexes via --batch / --serve mode.

cd ~/repos/gh/dictcli && ./run.sh stem "설계했다"     # → 설계
cd ~/repos/gh/dictcli && ./run.sh stem --serve 9876   # socket server (1ms/query)

Pipeline: "설계했다" → stem → "설계" → expand → ["design","architecture"]

Data

graph.edn: 3,971 triples, 2,449 :trans mappings, 4,728 words, 526 clusters
Sources: meta-note clusters, Syntopicon 102 Great Ideas, philosophy glossary
Relations: :trans(2449), :source(1422), :related(44), :synonym(44)

Architecture Note

Component	Runtime	Latency
expand/lookup/stats	GraalVM native-image	~9ms
stem	JVM (Kiwi JNI)	~1ms (server) / ~3s (cold start)

Native binary cannot include stem (JNI incompatible with native-image). Two separate execution paths — no conflict.

Layer 3 in the Stack

Layer	Tool	Role
1	knowledge_search	Embedding vector search
2	denotecli	Exact match + graph links
3	dictcli expand + stem	Korean→English query expansion + stemming

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tag-release

junghan0611/agent-config

Cut an OpenClaw-style CalVer snapshot tag. Tag loop = collect commits + closed NEXT.md items, move them to CHANGELOG.md, remove only those closed items from NEXT.md, then pre-flight/tag/push/stamp when explicitly requested. Not SemVer/deploy; doc/ops repos tag too. ROADMAP.md is optional/manual. Triggers: 태그 박자, 릴리즈 컷, changelog 정리, NEXT 비우자/갈무리, cut a release/tag, vYYYY.M.D[-suffix].

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jiracli

junghan0611/agent-config

Jira CLI for issue tracking, project management, and sprint/board operations on goqual-dev.atlassian.net. Supports multiple projects (MAT, DEVT, IOT, etc.). Also fetches Confluence wiki pages — import an Atlassian wiki URL (tinyLink or full /wiki/spaces/.../pages/<id>) into a local Markdown file with KST timestamps via the bundled confluence_ingest.py script (Confluence to Markdown, Atlassian wiki ingestion, wiki page import).

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bibcli

junghan0611/agent-config

Search/view local BibTeX entries. If only a source URL exists, use zotero-config (`server start` → `save` → `bib sync` → `bibcli search/show`) to recover a citation key before leaving orphan `#+print_bibliography:`.

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semantic-memory

junghan0611/agent-config

Semantic search over past sessions (pi + Claude Code) and the public digital garden md index (andenken md.lance, OpenRouter Qwen3-Embedding-8B 4096d). Uses LanceDB + hybrid retrieval (vector + FTS with score normalization). Korean↔English cross-lingual via dictcli expand. Recall tracking for memory consolidation. Use when searching for past conversations, decisions, context, or garden knowledge concepts.

2026-06-046

entwurf-peek

junghan0611/agent-config

sync entwurf 자식을 들여다보는 손. 호출자가 'Mattering...'에 묶여있을 때 자식 분신이 무엇을 하는지 확인. entwurf_peers는 control socket 있는 세션만 보여주는데, 이 스킬은 자식 entwurf 세션(이름 태그 entwurf)까지 합쳐서 본다. 트리거: 'entwurf-peek', '분신 들여다보기', '진행 중 세션', 'sync entwurf 안에서', 'peek session', 'live session map', '분신 추적'.

2026-06-046

forge

junghan0611/agent-config

포지(forge) — 셀프호스팅 Forgejo 이슈/PR/라벨/코멘트 작업면. 힣 에이전트가 코드 면에서 일하는 공유 손. botment의 자식 패턴(가든 댓글면 → 코드 댓글면 endpoint swap). 'forge', 'forgejo', '포지', 'issue', 'pull request', '이슈', '풀리퀘', '코드 댓글', '라벨'.

2026-06-046

name	dictcli
description	개인 어휘 그래프 — 한↔영 크로스링귀얼 쿼리 확장 + 한국어 형태소 분석. expand로 한글 단어에서 영어 태그 후보를 찾고, stem으로 한국어 어간을 추출한다. knowledge_search의 3층 역할. '단어 확장', '태그 찾기', '한영 매핑', 'expand', 'stem', '형태소'.

dictcli — Personal Vocabulary Graph (Layer 3)

Korean↔English triple graph. Expands Korean words to English Denote tags. Layer 3 of knowledge_search — cross-lingual query enrichment.

API

Binary bundled in skill directory. Must cd to {baseDir} (reads CWD/graph.edn).

Command	Usage	Output
expand	`cd {baseDir} && ./dictcli expand "보편" --json`	`["universal","universalism","particular","paideia"]`
graph	`cd {baseDir} && ./dictcli graph "보편"`	All triples for the word
stats	`cd {baseDir} && ./dictcli stats`	Graph statistics
validate	`cd {baseDir} && ./dictcli validate`	Invariant check

expand — Core Command

Traverses the graph: direct translation → opposite's translation → related word's translation.

cd {baseDir} && ./dictcli expand "기술" --json   # → ["art","technology","technique"]
cd {baseDir} && ./dictcli expand "도피" --json   # → ["escape","flight","avoidance","evasion"]

Empty array = word not in graph.edn. Fall back to original query.

knowledge_search Integration Pattern

1. User: "보편 학문 관련 노트"
2. expand "보편" → ["universal","universalism","paideia"...]
3. Search: "보편 학문 universal universalism paideia"

Agent autonomously: extract concept words → expand → enrich query → knowledge_search.

stem — Korean Morphological Analysis

JVM-only (Kiwi JNI — not in native binary). Called via dictcli repo's run.sh stem. Agents rarely call directly — andenken batch-indexes via --batch / --serve mode.

cd ~/repos/gh/dictcli && ./run.sh stem "설계했다"     # → 설계
cd ~/repos/gh/dictcli && ./run.sh stem --serve 9876   # socket server (1ms/query)

Pipeline: "설계했다" → stem → "설계" → expand → ["design","architecture"]

Data

graph.edn: 3,971 triples, 2,449 :trans mappings, 4,728 words, 526 clusters
Sources: meta-note clusters, Syntopicon 102 Great Ideas, philosophy glossary
Relations: :trans(2449), :source(1422), :related(44), :synonym(44)

Architecture Note

Component	Runtime	Latency
expand/lookup/stats	GraalVM native-image	~9ms
stem	JVM (Kiwi JNI)	~1ms (server) / ~3s (cold start)

Native binary cannot include stem (JNI incompatible with native-image). Two separate execution paths — no conflict.

Layer 3 in the Stack

Layer	Tool	Role
1	knowledge_search	Embedding vector search
2	denotecli	Exact match + graph links
3	dictcli expand + stem	Korean→English query expansion + stemming