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💹 Market & Finance Data

Deep Token Saverv1.0.0

Name: Deep Token Saver
Author: realpda

deep-token-saver

realpda

综合 token 节省方案。6层技术叠加，从输入/输出/记忆/上下文/审计全链路降本。含Caveman、L0/L1/L2分层、Remnic/QMD持久化、记忆去重、AGENTS压缩、Token审计。

cavemancost-reductionlatestoptimizationqmdremnictoken-saving

Download Package View on ClawHub

Installs (all time)

Installs (current)

Downloads

647

Stars

CreatedMay 5, 2026

UpdatedMay 11, 2026

Install & Quick Start

Install via ClawdBot CLI:

clawdbot install realpda/deep-token-saver

Skill Package1 files

📋SKILL.mdmarkdown

Failed to load file.

Quality Score

C42/100

Grade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.

Market Validation1/35

· 91 downloads (minimal demand)
· No tracked installs (may still have real users via manual install)

Documentation14/25

· SKILL.md present
· Moderate documentation (≥1500 chars)
· Detailed summary

Package Completeness6/15

· skillAssets present (0 files)

Security Analysis

💙 Low Risk

UNKNOWN_DATA_SINKhigh

Sends data to undocumented external endpoint (potential exfiltration)

POST → http://127.0.0.1:4318/engram/v1/consolidate

UNDOCUMENTED_EXTERNALlow

Calls external URL not in known-safe list

http://127.0.0.1:4318/engram/v1/consolidate

AI Analysis

The skill communicates only with localhost (127.0.0.1) endpoints for legitimate memory management and token optimization, not external servers. No credential harvesting, hidden override instructions, or obfuscation techniques are present; the external API usage is consistent with the stated purpose of memory consolidation and auditing.

Audited May 10, 2026 · audit v1.0

💡

Usage Guide

Generated Jul 30, 2026

AI application developersEnterprises with high-volume LLM usageintermediate

💡 Application Scenarios

Chatbot Token Cost ReductionCustomer Support

AI chatbots using large language models can reduce token usage by up to 75% per turn with output compression and 61% per session with input compression. Ideal for customer support or virtual assistants where high volume interactions rack up significant costs.

Long-Form Document AnalysisLegal & Research

When analyzing lengthy documents (e.g., legal contracts, research papers), hierarchical note compression (L0/L1/L2) can cut token consumption by 90% by loading only summaries first. Useful for legal tech or academic research tools.

Cross-Session Memory ManagementPersonal Assistants

Persistent memory across conversations via Remnic and QMD eliminates redundant memory loading, making it ideal for personal AI assistants that need to remember user preferences over long periods.

Cost-Efficient Code GenerationSoftware Development

Developers using AI for code generation can benefit from caveman mode which strips unnecessary words while preserving code blocks, paths, and numbers. This reduces output tokens without losing technical accuracy.

💼 Business Models

Subscription-Based SavingsRecurring subscription fees

Offer a premium tier where users' AI usage costs are reduced by 80-90% using this skill. Charge a monthly fee that is lower than the token savings, making it compelling for heavy users.

Token Audit as a ServicePer-report or monthly retainer

Provide token usage analytics and optimization reports to enterprises. The skill's audit layer can generate detailed savings reports, sold as a consultancy add-on.

Embedded Optimization SDKLicensing fees or per-API-usage

License the token-saving technology as a SDK for other AI platforms. Integrators pay per API call or a flat licensing fee to incorporate these layers into their products.

💬 Integration Tip

Start by enabling caveman mode for output compression, then set up Remnic server for persistent memory. The hierarchical note system works best for projects with structured documentation.