data-structure-protocol — security grade SAFE, quality 71/100

Security audit verdict: SAFE · quality 71/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by k-kolomeitsev · Codex Skill · ★ 65

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is data-structure-protocol safe to install? View the security audit →

About data-structure-protocol

[]() []() []() Data Structure Protocol (DSP) The missing memory layer for AI-assisted development The problem Your agent re-reads the same codebase every session. DSP fixes that. Every time you start a new task, your AI coding agent spends the first 5–15 minutes "getting oriented" — scanning files, tracing imports, figuring out what depends on what. On large projects this becomes a constant tax on tokens and attention. Context is rebuilt from scratch, every single time. DSP is a graph-based long-term structural memory stored in . It gives agents a persistent, versionable map of your codebase — entities, dependencies, public APIs, and the reasons behind every connection — so they can pick up exactly where they left off. DSP is not another workflow framework. It's the persistent structural memory layer that's missing from every AI coding workflow. Install macOS / Linux: bash curl -fsSL https://

agent-skillsaicaludeclaude-codecode-generationcode-reviewcodexcodex-skillscursorcursor-ai

Quick Facts

Stars65
Forks5
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score70.9478033834501/100
Last Updated2026-08-10
Created2026-02-20
Platformsclaude-code, codex, python
Est. Tokens~16k

Compatible Skills

These tools work well together with data-structure-protocol for enhanced workflows:

  • skill-forge — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • cursor-agent — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)
  • code-review-graph — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)
  • reviewd — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)

data-structure-protocol alternative? Top 6 similar tools

Looking for a data-structure-protocol alternative? If you're comparing data-structure-protocol with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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    103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf,

  • agent-skills by jdrhyne · ⭐ 241

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  • agent-skills by AsyrafHussin · ⭐ 70

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  • agent-skills by Nimbleway · ⭐ 52

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  • terrashark by LukasNiessen · ⭐ 323

    Terraform Skill for Claude Code and Codex. LLMs hallucinate a lot with Terraform - TerraShark fixes this. It e

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Frequently Asked Questions

What is data-structure-protocol?

data-structure-protocol is Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors. It is categorized as a Codex Skill with 65 GitHub stars.

What programming language is data-structure-protocol written in?

data-structure-protocol is primarily written in Python. It covers topics such as agent-skills, ai, calude.

How do I install or use data-structure-protocol?

You can find installation instructions and usage details in the data-structure-protocol GitHub repository at github.com/k-kolomeitsev/data-structure-protocol. The project has 65 stars and 5 forks, indicating an active community.

What license does data-structure-protocol use?

data-structure-protocol is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to data-structure-protocol?

The top alternatives to data-structure-protocol on Agent Skills Hub include awesome-ai-agent-skills, agent-skills, codex-settings. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools