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Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | officecli |
| description | Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents. |
AI-friendly CLI for .docx, .xlsx, .pptx. Single binary, no dependencies, no Office installation needed.
If officecli is not installed:
# macOS / Linux
curl -fsSL https://d.officecli.ai/install.sh | bash
# Windows (PowerShell)
irm https://d.officecli.ai/install.ps1 | iex
Verify with officecli --version. If still not found after install, open a new terminal.
L1 (read) → L2 (DOM edit) → L3 (raw XML). Always prefer higher layers. Add --json for structured output.
Before doc work, check Specialized Skills (bottom of this file). Fundraising decks, academic papers, financial models, dashboards, and Morph animations need their own skill loaded first — load_skill once, then proceed.
When unsure about property names, value formats, or command syntax, ALWAYS run help instead of guessing. One help query beats guess-fail-retry loops.
officecli help ≡ officecli --help, and officecli --help ≡ officecli help — same content.
officecli help # All commands + global options + schema entry points
officecli help docx # List all docx elements
officecli help docx paragraph # Full schema: properties, aliases, examples, readbacks
officecli help docx set paragraph # Verb-filtered: only props usable with `set`
officecli help docx paragraph --json # Structured schema (machine-readable)
Format aliases: word→docx, excel→xlsx, ppt/powerpoint→pptx. Verbs: add, set, get, query, remove. MCP exposes the same schema via the single command string param: {"command":"help docx paragraph"} (not a structured {"format":...,"type":...} object — the MCP tool has exactly one param, command, and passes it through to the CLI verbatim).
Every command auto-starts a resident on first access (60s idle timeout) — file-lock conflicts are automatically avoided. Explicit open/close is still recommended for longer sessions (12min idle):
officecli open report.docx # explicitly keep in memory
officecli set report.docx ... # no file I/O overhead
officecli close report.docx # save and release
Opt out of auto-start: OFFICECLI_NO_AUTO_RESIDENT=1.
Flush only at the non-officecli boundary. officecli's own reads (get/query/view/dump) always see your latest edits, so you never need to save mid-workflow. Run save (keeps the resident) or close (flush + release) only before a non-officecli program reads the file — python-docx/openpyxl, Word, a renderer, delivery/upload. (Idle sessions auto-flush within seconds; OFFICECLI_RESIDENT_FLUSH=each makes every mutation flush before returning.)
PPT:
officecli create slides.pptx
officecli add slides.pptx / --type slide --prop title="Q4 Report" --prop background=1A1A2E
officecli add slides.pptx '/slide[1]' --type shape --prop text="Revenue grew 25%" --prop x=2cm --prop y=5cm --prop font=Arial --prop size=24 --prop color=FFFFFF
Word:
officecli create report.docx
officecli add report.docx /body --type paragraph --prop text="Executive Summary" --prop style=Heading1
officecli add report.docx /body --type paragraph --prop text="Revenue increased by 25% year-over-year."
Excel:
officecli create data.xlsx
officecli set data.xlsx /Sheet1/A1 --prop value="Name" --prop bold=true
officecli set data.xlsx /Sheet1/A2 --prop value="Alice"
officecli create # Create blank .docx/.xlsx/.pptx (type from extension)
officecli view # outline | stats | issues | text | annotated | html
officecli get --depth N # Get a node and its children [--json]
officecli query # CSS-like query
officecli validate # Validate against OpenXML schema
| Mode | Description | Useful flags |
|---|---|---|
outline | Document structure | |
stats | Statistics (pages, words, shapes) | |
issues | Formatting/content/structure problems | --type format|content|structure, --limit N |
text | Plain text extraction | --start N --end N, --max-lines N |
annotated | Text with formatting annotations | |
html | Static HTML snapshot — same renderer as watch, no server needed | --browser, --page N (docx), --start N --end N (pptx) |
screenshot / svg / pdf / forms | PNG via headless browser / SVG (pptx slide) / PDF via exporter plugin / form-fields JSON via format-handler plugin | -o, --screenshot-width/-height, pptx --grid N |
Use view html for one-shot snapshots (CI artifacts, archival, diffing); use watch when you need live refresh or browser-side click-to-select.
Designed to assist users with ADHD (Attention Deficit Hyperactivity Disorder) by mitigating task paralysis, managing distractions, providing dopamine-driven progress tracking, and using executive-friendly visual formatting. Triggered by keywords or topics: - Focus/Distraction: "adhd", "fokus", "distracted", "gampang bosan", "pecah fokus", "distraksi", "sulit konsentrasi". - Task Initiation/Paralysis: "bingung mulai", "task paralysis", "mager", "banyak tugas", "tumpuk", "stuck", "overwhelmed". - Motivation/Rewards: "dopamine", "reward", "game", "poin", "xp", "checkpoint". - Formats: "bionic reading", "visual salience", "micro-step", "body double".
Execute detailed plans in batches with review checkpoints
Prevent task duplication, file conflicts, and coordination failures when multiple subagents work in parallel on the same Superagent project. Covers both Superagent→Subagent coordination and Master Agent→Superagent worktree coordination. Uses manage_plan and manage_tasks as the coordination hub.
Execute implementation plan by dispatching fresh subagent for each task, with code review between tasks
Create isolated git worktrees with smart directory selection and safety verification
Triggered when the agent needs to audit, discover, and resolve missing features, architectural or functional gaps, performance/process bottlenecks, and structural complexity liabilities across a codebase, delivering lean and pragmatic improvement blueprints.