DongHyeonkaandClaude Opus 5
1099834617
미추적 파일과 미커밋 수정을 전부 담아 pre-harness-removal 태그의 복구 범위를 확보한다. .agents/skills/writing-natural-korean 9개와 korean-technical-blog-skills-bundle-v1 61개가 여기 포함된다. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
36 lines
3.3 KiB
Plaintext
36 lines
3.3 KiB
Plaintext
9a1a4da5650006da39a0f0300aefb7ee1acc341fe99acfc6ae775f513a0c2b3a README.md
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89fef42eb8f2bb7ce5626c3303b49ec366413c7e8f3aa2d4552c1470559aed56 SKILL.md
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5a036ef405358370c3162d659f0900c33c588fb14fd1be71513e3cc13e5db377 examples/end-to-end-performance-case.md
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a800700eacc32f834736f082380687f65a962de72c7aff1b29ea132bb03ba5c1 examples/revision-pairs.jsonl
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26473dddaa0695d5a0dbd7c6d9a3da77dfd99e686650a27d789f51d4929a12bc lexicons/formulaic-openings-and-closings.yaml
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741bf512903ed0bcdb3c43dc4575c65e00bd6fd413fe238b9ce331eb8e751c29 lexicons/product-names.example.yaml
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db4c48c7d0a6c20c46f7ea82fb9ba28a645462a5e2f045498703f4ada746437e lexicons/protected-identifiers.example.yaml
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0eee62d3891f6499b2682e36a9418297d6aec66c9217440504e1dc9a2b52d18b lexicons/vague-expressions.yaml
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910c52906d19bd29c068f9696f2edcc81c2149d4c06b6bb3ee052eb048921667 profiles/architecture-decision.yaml
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2b8a37f5dc61af83fd224ce25be614f5d6f30b7a9ca9af768b64d0c3d56b77ac profiles/conversational-tech.yaml
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557ea745b8c517d8535b9787399245317a98c328b9a2da3b00f2e393d6a19113 profiles/default-formal.yaml
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86528843f3efc5288121dfa2b1b13db1c1ed90c27334d0e3fe65b53802435b34 profiles/incident-postmortem.yaml
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3f59159555be2e300c0944f36b5753228232064ce89daf11acc4212c1a2a5cd5 profiles/migration-case-study.yaml
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1635d41c396bbb5f133c9c6a3535f76f7d5bd61f5a67f029d53cf0829d4f5c62 profiles/performance-case-study.yaml
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d4be41789818f1cdafed59f24a1d18a719153f48bfb1d9024888d356f9261f4e profiles/recruitment-tech-content.yaml
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52412ea45369baad5d0f715bc45e0abcf3de0d87184d3e6e1b491cf98f384c25 profiles/tooling-adoption.yaml
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77f56eefa54db15f00adede694a0f7f61a1c2d87464ca12cfc0365bc8c817b58 profiles/tutorial-lab.yaml
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407136db136e7a27afc4a5c6ed635a0d479b5b4372370fd8af3a44ab94c4bdfd references/decision-policy.md
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58013844347c1e02a7183a4320e000cfef089d29e704f054f4a5bc7f40919ff0 references/enterprise-blog-patterns.md
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0846e1b5293de602e15f52dec4f9776f5e302d101df4abd8356b69b6186492b5 references/evidence-and-source-policy.md
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ba935624b8d143d573c85a05f4d931ec6bda9959ce3ef48eb69ff6b55b44a6ea references/exceptions.md
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97f93c70523bf0cc1fcf0cad351a69b48d702420bd45bbc2841c6236df1a794e references/output-modes.md
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849fba1475eac2ff5258e80be8a3f1cc9cd49c013ca9ed703b5a8ac112bf4b60 references/rule-catalog.md
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3b933fa88f52f5e596f8231b0b128d5ca86b28cc452db91864a66e3d3d3b79a4 references/source-basis.md
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88047b6409edb2b1e8705b1a5431bbb7f594ef8cb32fd43765a6c5d03da39803 references/structure-patterns.md
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db85244892b698fc3dc424972920074f43f970d4ebccc09354eb1f3a891ce0d8 references/titles-introductions-conclusions.md
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c110176b07a4a4edf75c9aa6edc374e08250be9a27bef0823b2f41ed085d6b8d schemas/article-brief.schema.json
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417548ed4936633bdff7fb4aa87683130636932dfebe44c541c4b0fd426deb70 schemas/article-result.schema.json
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9537896cb1914a8b6537aaa6b27d51b0e06e94bc60280a8ff1990f5904e4532c schemas/rubric.schema.json
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ccd2fbe9b8c87af814eae9790df863b50b93f518cc1ba871ef2930ddac54c3e3 scripts/validate_skill.py
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343d04ca2c1f5139a94176420417d5481aeaccfefdf6f4f09cd31a1654ed1201 tests/baseline-observations.md
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50772b7b691fc86631b5e4ae35997d9c9ef056662eb43a76500c9ff27c239a09 tests/cases.json
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03e73c9a515449f2a8a0162d1b90176f23d75efbf5d2ef255592dd8cf39a9d21 tests/evaluation-rubric.md
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cfb996bb669ac09e3ffded859f421c8f30162c34eedf69446a6c85f9876bd961 tests/pressure-scenarios.md
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6605eef379ba9e91d2ee4a60a9b28b36aa50a87037c89264afc601cf59515949 tests/workflow.jsonl
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