Token Saver (English) — Cut Your AI Context Cost

    2

    Audit and reduce token consumption by slimming standing instructions and throttling runtime file reads.

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    Works with the AI tools you already use

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

    Token Saver (English) — Cut Your AI Context Cost

    Example session with this skill installed

    My CLAUDE.md is getting huge and the agent is starting to ignore my project rules. Can you audit the standing context and suggest how to slim it down?

    • Read your context and instructions
    • Compiled the token saver english
    • Generated the document

    I have audited your project instructions using the token_meter.py script against the Claude Code guidance.

    Standing-context audit

    Current harness: Claude Code
    Budget: 200 lines (Guideline)

    FileBytesEst. TokensCurrent LinesRisk
    CLAUDE.md8,4202,105245High (Truncation)
    AGENTS.local.md1,20030035Normal

    Expected after slimming: 8,420 -> 3,150 bytes (estimated)

    Edit proposals awaiting confirmation

    1. CLAUDE.md lines 110-165: Move the "Legacy API Documentation" section to a new file docs/legacy_api.md.

      • Expected saving: 2,800 bytes / 55 lines.
      • Reason: This content is rarely accessed and crowds out active coding rules.

    2. CLAUDE.md lines 12-40: Consolidate redundant style rules.

      • Current: 5 separate bullets for indentation and spacing.
      • Suggested: "Follow Prettier config; use 2-space indents, no semicolons."
      • Expected saving: 450 bytes.

    3. CLAUDE.md lines 180-210: Move troubleshooting tables to references/errors.md.

      • Expected saving: 2,020 bytes / 30 lines.

    Next steps

    • Provide a yes to apply the migration of legacy docs to docs/legacy_api.md.
    • Confirm if I should proceed with the phrasing compression for style rules.
    • Run python3 scripts/token_meter.py doctor to ensure measurement precision.

    token-saver-english-cut-your-ai-context-.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

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

    What you get

    Reduce token spend by slicing large file reads and log outputs.Audit project instructions against harness-specific byte and line limits.Prevent context overflow by proposing diffs to compress instruction files.Identify when a session should be cleared to maintain agent performance.

    About this skill

    The problem

    Large project instruction files like CLAUDE.md or AGENTS.md grow until they hit context limits or crowd out working memory. Coding agents often waste tokens by reading entire files when only a small range is needed.

    What it does

    • Audits standing context files against specific harness budgets for Codex, DeepSeek, and Claude Code.
    • Generates diff proposals to slim down instructions by removing duplication and moving details to reference files.
    • Throttles runtime token usage by using Grep to locate specific lines before reading large files.
    • Intercepts large command outputs by redirecting to disk and slicing results instead of flooding the chat.
    • Provides a Python-based token meter to accurately measure usage or provide weighted estimates when tokenizers are unavailable.

    Frameworks & tools

    Works with Claude Code, DeepSeek Harness, Codex, and WorkBuddy. Uses Python 3.10 standard library, tiktoken for precision, and shell utilities like grep, sed, and jq.

    Why this beats prompting it yourself

    Standard agents naturally default to reading full files and dumping long logs, which rapidly exhausts context windows. This skill enforces a "slice-first" strategy and budget-aware auditing that prevents silent truncation of critical instructions.

    Use cases

    • Compressing a bloated CLAUDE.md that has exceeded the 200-line recommended limit.
    • Reducing API costs by preventing the agent from re-reading files already in the session.
    • Auditing project instructions to see which files are at risk of being ignored by the harness.
    • Managing long-running test suites by capturing logs to disk and only surfacing error traces.

    Known limitations

    Never modifies session history or instruction files directly. Edits require human confirmation. Measurement accuracy drops for CJK characters if tiktoken is not installed.

    How to install

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

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    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.

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    Security scanned

    Verified clean 25 days ago

    • Passed all security checks, Safe to install

    Listed25 days ago

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