菜单
Manage tasks and features on the JSON-based project boards. Use for creating, updating, querying, and archiving tasks and features. Triggers on requests like "create task", "update task status", "query tasks", "create feature", "update feature", "query features".
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Young-Z/X-IPE --skill x-ipe-tool-task-board-manager命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
基于 SOC 职业分类
| name | x-ipe-tool-task-board-manager |
| description | Manage tasks and features on the JSON-based project boards. Use for creating, updating, querying, and archiving tasks and features. Triggers on requests like "create task", "update task status", "query tasks", "create feature", "update feature", "query features". |
Provides CRUD operations for the JSON-based task board and feature board. All project tracking data is stored as JSON files managed by Python scripts with atomic file operations and concurrency-safe locking.
| Board | Location | Format |
|---|---|---|
| Tasks | x-ipe-docs/planning/tasks/ | Daily files tasks-YYYY-MM-DD.json + tasks-index.json |
| Features | x-ipe-docs/planning/features/features.json | Single file with all features |
All scripts are in .github/skills/x-ipe-tool-task-board-manager/scripts/.
| Script | Purpose | Example |
|---|---|---|
task_create.py | Create a new task | uv run python scripts/task_create.py --title "Fix bug" --description "..." --assignee "Drift" |
task_update.py | Update task fields | uv run python scripts/task_update.py TASK-123 --status done |
task_query.py | Query/search tasks | uv run python scripts/task_query.py --status in_progress |
task_archive.py | Archive a task | uv run python scripts/task_archive.py TASK-123 |
| Script | Purpose | Example |
|---|---|---|
feature_create.py | Create a new feature | uv run python scripts/feature_create.py --epic-id EPIC-055 --feature-id FEATURE-055-A --title "..." --status Planned |
feature_update.py | Update feature fields | uv run python scripts/feature_update.py FEATURE-055-A --status Completed |
feature_query.py | Query/search features | uv run python scripts/feature_query.py --epic-id EPIC-055 |
| Script | Purpose | Example |
|---|---|---|
migrate.py | Migrate from markdown boards to JSON | uv run python scripts/migrate.py --all --dry-run |
_board_lib.py provides the foundation:
resolve_data_path(board_type) — Locates data directoryatomic_read_json(path) / atomic_write_json(path, data) — Thread-safe I/Owith_file_lock(path) — fcntl-based file lockinggenerate_task_id() / validate_task(data) / validate_feature(data) — ID generation & schema validationtask_id: "TASK-XXX" # Auto-generated sequential ID
title: "Task title"
description: "Detailed description"
status: "pending | in_progress | done | blocked | cancelled"
assignee: "Agent nickname"
created_at: "YYYY-MM-DD"
updated_at: "YYYY-MM-DD"
output_links: [] # Paths to artifacts produced
next_task: "" # Follow-up task reference
_version: "1.0"
feature_id: "FEATURE-XXX-Y"
epic_id: "EPIC-XXX"
title: "Feature title"
status: "Planned | Refined | Designed | Implemented | Tested | Completed | Retired"
version: "1.0"
description: ""
dependencies: []
artifact_links: []
_version: "1.0"
# Creating a task
Use x-ipe-tool-task-board-manager to create a task:
uv run python .github/skills/x-ipe-tool-task-board-manager/scripts/task_create.py \
--title "TASK_TITLE" --description "TASK_DESC" --assignee "NICKNAME"
# Updating task status
Use x-ipe-tool-task-board-manager to update task:
uv run python .github/skills/x-ipe-tool-task-board-manager/scripts/task_update.py \
TASK-XXX --status done
# Querying tasks
Use x-ipe-tool-task-board-manager to query tasks:
uv run python .github/skills/x-ipe-tool-task-board-manager/scripts/task_query.py \
--status in_progress --assignee "NICKNAME"
fcntl.flock file locking*.archived.json; features use Retired statusCentral orchestrator for the knowledge pipeline. Discovers available knowledge skills at runtime, classifies requests, routes to constructors/extractors/ontology skills, and drives the full 格物致知 workflow. Triggers on requests like "build a user manual", "extract knowledge", "run knowledge pipeline", "discover ontology graphs".
Observe and record user behavior on websites via Chrome DevTools MCP. Injects tracker IIFE, captures DOM events with PII masking, and produces structured observation summaries. Triggers on operations like "start_tracking", "stop_tracking", "get_observations".
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.