ai context pack compiler

    1

    Compiles messy, contradictory instructions into compact, hierarchy-preserving agent context packs.

    $5

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    ai context pack compiler

    Example session with this skill installed

    Compile a context pack from my CLAUDE.md which says 'Always use TypeScript', but my notes.txt says 'Use vanilla JS for prototypes' and 'Never use semicolons'. Prototypes are the current focus.

    • Read your context and instructions
    • Compiled the ai context compiler

    I have processed your CLAUDE.md and notes.txt. I resolved the language contradiction by prioritizing the "prototype" scope defined in your notes, which overrides the general TypeScript requirement.

    Context Pack v1

    Goals

    • [GOAL-01] Develop prototype using vanilla JavaScript.

    Invariants

    • [INV-01] Never use semicolons in any JavaScript files.
    • [INV-02] Code must be executable in a standard Node.js environment.

    Variables

    • [VAR-01] scope = prototype (required, default: prototype)
    • [VAR-02] language = vanilla JavaScript (required)

    Priorities

    1. [PRIO-01] Use [VAR-02] over TypeScript when [VAR-01] is active.

    Workflow

    Stage 1: Scaffolding
    • input: [VAR-01], [VAR-02]
    • steps: Initialize project without TypeScript configuration.
    • output: package.json and index.js

    Output Format

    • Format: Plain JavaScript
    • Prohibited: TypeScript transpilation steps, semicolons.

    Validation Report

    • Compression: 450 chars → 180 chars (60% reduction)
    • Contradictions: 1 resolved (Scope-specific JS over general TS), 0 unresolved
    • Completeness: pass
    • Hierarchy: pass
    • Faithfulness: yes — Correctly prioritized the specific "prototype" constraint over general project rules.

    Next steps

    1. Copy the "Context Pack v1" content into your agent's system instructions.
    2. Verify if any additional environment variables are needed for the prototype.
    3. Run a linter check to ensure the no-semicolon invariant is enforced.
    I have processed your CLAUDE.md

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

    About this skill

    The problem

    Large instruction files, conflicting CLAUDE.md notes, and verbose prompts lead to agents ignoring hard constraints or hallucinating requirements. As project context grows, agents struggle to prioritize contradictory rules buried in deep prose.

    What it does

    • Extracts goals, invariants, variables, and dependencies from raw markdown or URL dumps.
    • Deduplicates instructions with over 80% semantic overlap to reduce token waste.
    • Resolves logic contradictions by prioritizing specific conditions over general rules.
    • Reorders instructions into a deterministic hierarchy, placing dependencies and invariants first.
    • Generates a machine-parseable Context Pack with a built-in validation report.

    Why this beats prompting it yourself

    Manual prompt compression often accidentally strips edge-case constraints that seem redundant but are critical for execution. This skill uses a formal classification procedure to ensure every invariant is preserved while achieving 40-85% character reduction.

    Use cases

    • Consolidating overlapping SOUL.md, CLAUDE.md, and README instructions into one system prompt.
    • Creating a deterministic context file for a multi-agent pipeline.
    • Refactoring a prompt that an agent is currently failing to follow consistently.
    • Auditing complex workflows for unresolved logic contradictions before deployment.

    Known limitations

    Requires input to contain at least one imperative sentence. It will not generate new goals or creative content not implied by the source text.

    Requires input text with at least one imperative or constraint. Cannot execute the workflow or invent goals. Explicitly avoids creative writing or goal generation.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 1 month ago

    Permissions

    Terminal / Shell
    Browser
    Listed1 month ago

    What's inside

    Frequently Asked Questions

    The AI Context Pack Compiler identifies contradictory instructions and resolves them by prioritizing specific constraints over general rules, ensuring your agent follows the most relevant logic first.

    The skill produces a compact, machine-parseable context file accompanied by a validation report that highlights which instructions were prioritized or deduplicated.

    This skill is agent-agnostic and works with any LLM (like Claude, GPT-4, or Llama) that utilizes system prompts, CLAUDE.md files, or structured context windows.

    While it significantly reduces token counts by deduplicating overlapping prose, its primary goal is maintaining the structural integrity of your 'invariants' or hard rules that manual compression often loses.

    Setup is minimal; once added to your workspace, you simply feed the skill your raw markdown files or URLs, and it automatically begins the classification and hierarchy reordering process.

    The compiler requires at least one imperative instruction to function, as it is designed to organize existing logic rather than generate new creative content or goals from scratch.

    New in Prompt & Skill Engineering