Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    Doc to Agent Knowledge Architect

    1

    Autonomous agent memory architect. Converts messy Notion dumps, PRDs, and codebases into token-optimized, hallucination-resistant _Knowledge/ agent memory layers.

    $19

    Secure checkout via Stripe

    30-day refund guarantee

    Converts to your local currency at checkout

    0 installsSecurity scanned
    Doc to Agent Knowledge Architect

    Doc to Agent Knowledge Architect

    Example session with this skill installed

    Analyze my repo and this 30-page PDF spec to build a _Knowledge/ structure with KEY_CONTEXT.md, ARCHITECTURE.md, and a REPO_MAP.md optimized for Claude Code.

    • Read your context and instructions
    • Compiled the doc to agent

    I have audited the repository and the provided specification. I filtered approximately 12,000 tokens of redundant prose and marketing descriptions, synthesizing them into a high-density _Knowledge/ architecture.

    Agent Knowledge Architecture

    _Knowledge/
├── KEY_CONTEXT.md          # Active Mission: Migration to Next.js 15 + Tailwind 4
├── ARCHITECTURE.md         # Data Flow: Edge Functions -> Supabase Auth -> PG
├── REPO_MAP.md             # Index: /src/components (UI), /src/lib (Logic)
└── CLAUDE.md               # System Instructions & Constraints

    KEY_CONTEXT.md (Snippet)

    EntityConstraint/Value
    Node Versionv20.x
    Primary FrameworkNext.js 15 (App Router)
    Strict RuleNo any types in TypeScript. Use Zod for all API validation.
    AuthSupabase Auth (Environment: ${NEXT_PUBLIC_SUPABASE_URL})

    ARCHITECTURE.md (Data Flow)

    graph TD
    Client -->|JWT| Edge[Vercel Edge Function]
    Edge -->|Query| DB[(PostgreSQL)]
    Edge -->|Event| Hook[Stripe Webhook]

    REPO_MAP.md

    • /src/components: Atomic UI components using Shadcn.
    • /src/hooks: Custom React hooks for data fetching and state.
    • /src/lib/db.ts: Prisma client singleton and schema definitions.
    • /public/assets: Static images and localized JSON strings.

    Next steps

    1. Review KEY_CONTEXT.md to ensure all architectural invariants match your local environment.
    2. Commit the _Knowledge/ directory to your repository.
    3. Update your .clauderc or CLAUDE.md to point the agent to these files for every session.
    KEY_CONTEXT.md

    Connects securely to your tools. The creator never sees your data.

    What you get

    Partition messy docs into fast-lookup modules for reduced latency.Compress 50-page specs into high-density 1,200-token cognitive anchors.Establish a DAILY_HANDOFF.md for seamless multi-session state transfer.Generate ARCHITECTURE.md with Mermaid diagrams from unstructured text.

    About this skill

    The problem

    Large project contexts, messy Notion exports, and 50-page PRDs cause AI agents to hallucinate, lose focus, or hit token limits. Raw documentation is often too verbose for efficient agent reasoning, leading to wasted credits and incorrect code generation.

    What it does

    • Audit and filter redundant prose from documentation to extract core technical invariants.
    • Construct a modular _Knowledge/ directory including executive briefs, repo maps, and decision logs.
    • Compress high-density information into specific token budgets to stay within context windows.
    • Embed zero-assumption markers and negative constraints to prevent agent hallucinations.
    • Generate handoff protocols and system prompt snippets for persistent multi-session memory.

    Frameworks & tools

    Designed for Claude Code, Cursor, Windsurf, Gemini CLI, Antigravity, and OpenHands. Optimizes documentation for LLMs via Markdown, Mermaid diagrams, and ADR tables.

    Why this beats prompting it yourself

    Manual documentation cleanup is tedious and rarely follows a deterministic architecture. This skill applies a rigid, multi-phase engineering workflow to ensure your agent's memory layer is token-efficient, hierarchical, and structured specifically for machine consumption rather than human reading.

    Use cases

    • Onboarding an AI agent to a legacy codebase with zero existing documentation.
    • Converting a sprawling product requirement document into actionable agent constraints.
    • Setting up a stateful DAILY_HANDOFF.md for persistent memory across long dev sessions.
    • Creating a deterministic REPO_MAP.md to stop agents from wasting tokens on file exploration.

    Known limitations

    Cumulative knowledge layer is targeted at a 5,500 token footprint. Extremely large repositories may require multiple partitioned knowledge modules.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

      Free skills download straight away. Paid skills unlock right after purchase.

    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    30-day refund

    Not a fit? Get your money back

    Trust & safety

    Security scanned

    Verified clean 23 days ago

    • Passed all security checks, Safe to install

    Listed23 days ago

    What's inside

    Frequently Asked Questions