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para-pkm

Manage PARA-based personal knowledge management (PKM) systems using Projects, Areas, Resources, and Archives organization method. Use when users need to (1) Create a new PARA knowledge base, (2) Organize or reorganize existing knowledge bases into PARA structure, (3) Decide where content belongs in PARA (Projects vs Areas vs Resources vs Archives), (4) Create AI-friendly navigation files for knowledge bases, (5) Archive completed projects, (6) Validate PARA structure, or (7) Learn PARA organizational patterns for specific use cases (developers, consultants, researchers, etc.)

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Manage PARA-based personal knowledge management (PKM) systems using Projects, Areas, Resources, and Archives organization method. Use when users need to (1) Create a new PARA knowledge base, (2) Organize or reorganize existing knowledge bases into PARA structure, (3) Decide where content belongs in PARA (Projects vs Areas vs Resources vs Archives), (4) Create AI-friendly navigation files for knowledge bases, (5) Archive completed projects, (6) Validate PARA structure, or (7) Learn PARA organizational patterns for specific use cases (developers, consultants, researchers, etc.)

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, references/ai-navigation.md, references/common-patterns.md, references/decision-guide.md, references/para-principles.md, scripts/archive_project.py

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 12 sections Open source page

PARA PKM

Organize by actionability, not topic. Projects/Areas/Resources/Archives for optimal AI navigation. Monthly review cadence.

Core Concepts

Projects = Time-bound goals with deadlines (completes โ†’ Archives); includes projects/stories/ for job applications Areas = Ongoing responsibilities (use _overview.md per area for context) Resources = Reference material; when unsure, put here temporarily Archives = Inactive items from any category

Decision Tree

Has deadline/end state? โ†’ Projects Ongoing responsibility? โ†’ Areas Reference material? โ†’ Resources (default for uncertain items) Completed/inactive? โ†’ Archives

Quick Start

python scripts/init_para_kb.py <name> - Creates PARA + projects/stories/ + navigation Identify projects (deadlines) โ†’ areas (ongoing) โ†’ resources (reference) python scripts/generate_nav.py - Generate AI navigation

Scripts

ScriptPurposeUsageinit_para_kb.pyScaffold new KB<name> [--path <dir>]validate_para.pyCheck structure, detect anti-patterns[path]archive_project.pyArchive with metadata (date, origin)<project-file> [--kb-path]generate_nav.pyCreate AI nav (<100 lines)[--kb-path] [--output]

Templates

TemplatePurposeassets/AGENTS.md.templateAI navigation indexassets/project.md.templateProject file structureassets/area-overview.md.templateArea _overview.md formatassets/README.md.templateKnowledge base README

Patterns by Role

Developers: projects/active/ features/bugs, areas/professional-development/, resources/coding-standards/ Consultants: projects/active/ deliverables + projects/stories/, areas/consulting/clients/, resources/templates/ Researchers: projects/active/ papers/grants, areas/research-program/, resources/literature-review/ Product Builders: projects/active/ launches, areas/product-development/{active,research,graduated,legacy}/

Complex Scenarios

Client = project + relationship: projects/active/client-x.md (deliverables) + areas/consulting/clients/client-x.md (relationship, billing) Research lifecycle: areas/product-development/{research โ†’ graduated โ†’ active โ†’ legacy} with cross-references

Anti-Patterns

inbox/ folder (capture directly into PARA; use Resources when uncertain) Deep nesting (max 2-3 levels; flat > nested) Topic-based organization ("work/personal" โ†’ use actionability) Todo folders (tasks belong with their projects/areas) Perfectionism (move freely as understanding evolves; monthly review catches misplacements)

Content Lifecycle

Resources โ†’ Projects โ†’ Archives (research โ†’ active work โ†’ completed) Areas โ†’ Archives (no longer responsible) Projects โŸบ Areas (goal becomes ongoing or vice versa)

AI Navigation & Success Tips

Keep nav under 100 lines; point to paths not files; minimize tokens Start simple ("What am I working on now?"); one home per item (use links) Monthly review: archive completed, reassess areas; let patterns emerge

References

para-principles.md - Complete PARA method, "actionability not topic" principle decision-guide.md - Detailed decision tree with edge cases common-patterns.md - Proven patterns for different roles ai-navigation.md - AI-friendly navigation best practices

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
5 Docs1 Scripts
  • SKILL.md Primary doc
  • references/ai-navigation.md Docs
  • references/common-patterns.md Docs
  • references/decision-guide.md Docs
  • references/para-principles.md Docs
  • scripts/archive_project.py Scripts