{"id":"d892318c-47ec-4b27-8f6b-76348cf4a2c3","shortId":"hwKmhf","kind":"skill","title":"draft","tagline":"Writes a complete IMRaD-structured academic paper draft (Abstract, Introduction, Related Work, Methods, Results, Discussion, Conclusion, References) from the user's notes, documents, and wiki content. Use when the user asks to write a paper, create a manuscript, generate a draft,","description":"# Paper Draft Generation\n\nGenerate a complete IMRaD-structured academic paper draft from research notes and documents.\n\n## IMRaD Structure\n\n| Section | Purpose | Length |\n|---------|---------|--------|\n| **Abstract** | Background, objective, methods, findings, conclusions | 250–300 words |\n| **Introduction** | Problem, motivation, gap, contribution | 400–600 words |\n| **Related Work** | Prior literature organized by theme | 500–800 words |\n| **Methods** | How the research was/will be conducted | 400–600 words |\n| **Results** | What was found (or projected findings) | 300–500 words |\n| **Discussion** | Interpretation, implications, limitations | 400–600 words |\n| **Conclusion** | Summary, contributions, future work | 200–300 words |\n| **References** | All cited sources | As needed |\n\n## Workflow\n\n1. **Gather content** — read all provided notes, wiki pages, and documents\n2. **Identify the core contribution** — what is new and why does it matter?\n3. **Map citations** — track which sources support which claims\n4. **Draft section by section** — follow IMRaD order\n5. **Add inline citations** — use `[Author, Year]` or `[Source Title]` format\n6. **Flag gaps** — mark sections needing real data with `> ⚠️ [PROJECTED — add empirical data]`\n\n## Citation format\n\nUse the actual title or author of notes/documents you read:\n\n```markdown\nPredictive coding theory proposes... [Rao & Ballard, 1999]\n```\n\nAt the end, add a References section listing all cited sources.\n\n## Handling missing data\n\nWhen the research doesn't have empirical results yet, write projected results based on the hypotheses — but clearly mark them:\n\n```markdown\n> ⚠️ **Projected Results** — Replace with actual experimental data before submission.\n\nBased on the experimental design, we expect...\n```\n\n## Quality checklist\n\n- [ ] Abstract covers all 5 components (background, objective, methods, findings, conclusions)\n- [ ] Introduction ends with a clear statement of contribution\n- [ ] Every major claim has an inline citation\n- [ ] Methods section is specific enough to reproduce\n- [ ] Discussion addresses alternative interpretations\n- [ ] Limitations section is honest, not 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chars)","verified":false,"liveness":"unknown","lastLivenessCheck":null,"agentReviews":{"count":0,"score_avg":null,"cost_usd_avg":null,"success_rate":null,"latency_p50_ms":null,"narrative_summary":null,"summary_updated_at":null},"enrichmentModel":"deterministic:skill-github:v1","enrichmentVersion":1,"enrichedAt":"2026-05-18T18:58:32.286Z","embedding":null,"createdAt":"2026-05-15T13:05:44.858Z","updatedAt":"2026-05-18T18:58:32.286Z","lastSeenAt":"2026-05-18T18:58:32.286Z","tsv":"'1':135 '1999':219 '2':146 '200':125 '250':72 '3':159 '300':73,110,126 '4':168 '400':80,100,117 '5':176,276 '500':90,111 '6':187 '600':81,101,118 '800':91 'abstract':11,66,273 'academ':8,53 'actual':204,259 'add':177,197,223 'address':306 'altern':307 'ask':33 'author':181,207 'background':67,278 'ballard':218 'base':246,264 'checklist':272 'citat':161,179,200,297 'cite':130,229 'claim':167,293 'clear':251,287 'code':214 'complet':4,49 'compon':277 'conclus':18,71,120,282 'conduct':99 'content':28,137 'contribut':79,122,150,290 'core':149 'cover':274 'creat':38 'data':194,199,233,261 'defens':314 'design':268 'discuss':17,113,305 'document':25,60,145 'doesn':237 'draft':1,10,43,45,55,169 'empir':198,240 'end':222,284 'enough':302 'everi':291 'expect':270 'experiment':260,267 'find':70,109,281 'flag':188 'follow':173 'format':186,201 'found':106 'futur':123 'gap':78,189 'gather':136 'generat':41,46,47 'handl':231 'honest':312 'hypothes':249 'identifi':147 'implic':115 'imrad':6,51,61,174 'imrad-structur':5,50 'inlin':178,296 'interpret':114,308 'introduct':12,75,283 'length':65 'limit':116,309 'list':227 'literatur':86 'major':292 'manuscript':40 'map':160 'mark':190,252 'markdown':212,254 'matter':158 'method':15,69,93,280,298 'miss':232 'motiv':77 'need':133,192 'new':153 'note':24,58,141 'notes/documents':209 'object':68,279 'order':175 'organ':87 'page':143 'paper':9,37,44,54 'predict':213 'prior':85 'problem':76 'project':108,196,244,255 'propos':216 'provid':140 'purpos':64 'qualiti':271 'rao':217 'read':138,211 'real':193 'refer':19,128,225 'relat':13,83 'replac':257 'reproduc':304 'research':57,96,236 'result':16,103,241,245,256 'section':63,170,172,191,226,299,310 'skill' 'skill-draft' 'sourc':131,164,184,230 'source-richard-kim-79' 'specif':301 'statement':288 'structur':7,52,62 'submiss':263 'summari':121 'support':165 'theme':89 'theori':215 'titl':185,205 'topic-academic' 'topic-agent-skills' 'topic-claude' 'topic-hypothesis' 'topic-peer-review' 'topic-research' 'topic-science' 'track':162 'use':29,180,202 'user':22,32 'was/will':97 'wiki':27,142 'word':74,82,92,102,112,119,127 'work':14,84,124 'workflow':134 'write':2,35,243 'year':182 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research agent skills for Claude Code and other Agent Skills-compatible tools. Hypothesis generation, experiment design, paper drafting, peer review simulation, and more.","skill_md_sha":"1e692d4a77c6e4a04bc41a09b2296142b72df33f","skill_md_path":"skills/draft/SKILL.md","default_branch":"main","skill_tree_url":"https://github.com/richard-kim-79/archora-skills/tree/main/skills/draft"},"layout":"multi","source":"github","category":"archora-skills","frontmatter":{"name":"draft","license":"MIT","description":"Writes a complete IMRaD-structured academic paper draft (Abstract, Introduction, Related Work, Methods, Results, Discussion, Conclusion, References) from the user's notes, documents, and wiki content. Use when the user asks to write a paper, create a manuscript, generate a draft, or produce academic writing. Do NOT use for short summaries — only for full paper-length output."},"skills_sh_url":"https://skills.sh/richard-kim-79/archora-skills/draft"},"updatedAt":"2026-05-18T18:58:32.286Z"}}