Enterprise DNAEnterprise DNA

Skills

principle-encode-lessons-in-structure

by michael-denyer

Antigravity, Claude Code, Codex, Copilot, Gemini, Muse, OpenCode, Pi, and Prime Agent versions of Poteto's pstack.

Visit michael-denyer ↗

Our verdict

Not reviewed yet

We have not reviewed principle-encode-lessons-in-structure yet

No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.

How we review records

From the listing

About principle-encode-lessons-in-structure

Antigravity, Claude Code, Codex, Copilot, Gemini, Muse, OpenCode, Pi, and Prime Agent versions of Poteto's pstack. Rigorous agent workflows with Cursor primitives translated for other harnesses.

Best for

Developers using multiple AI coding agents who want consistent structural practices.

Use cases

  • Enforce consistent code structure across projects
  • Translate Cursor-based workflows to other AI agents
  • Apply structural lessons in multi-agent environments

Notes

4,171 stars on GitHub. Last updated 2026-11-09. Licensed MIT.

Indexed from github-skill-repos. Verified against the live GitHub repo.

Pros

  • Supports a wide range of popular AI coding tools
  • Based on proven pstack workflows
  • Written in JavaScript, easy to integrate

Cons

  • Requires understanding of each harness's primitives
  • May need adaptation for non-Cursor workflows
  • Limited to writing and structural guidance, not a full framework

Key facts

What we have checked

Days since the last commit
0
Checked GitHub
GitHub forks
372
Checked GitHub
GitHub stars
4,117
Checked GitHub
Days to a first reply on issues
0.1
Checked GitHub
Open issues
4
Checked GitHub
Releases in the last 90 days
89
Checked GitHub

Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.

Stars and usage

How principle-encode-lessons-in-structure is growing

GitHub stars

3,712 to 4,117

stars. 1 Nov 2026 to 7 Nov 2026, 2 readings.

Source: GitHub. Checked .

Health and security

Is principle-encode-lessons-in-structure looked after, and what do its setup files show

Health score

81 out of 100

Does someone look after this repository? It does not say the code is good or safe. Worked out from GitHub signals checked . How it is worked out

PartPointsWhat we saw
Recent activity30 of 30Last push 0 days ago
Releases15 of 1589 releases in 90 days
Issue replies20 of 20First reply in 0.1 days (median)
Maintainer0 of 15Owned by a single user
Official sourceNot countedMCP servers only

Security check static checks

100 out of 100

Reads what is published about the server: package advisories, licence, secrets in the documented setup and tool permissions. Nothing is installed or run, so this is not a security assessment. Checked by edna-skill-static-v1 main@356c6e0f978d. What it checks

  • Note No dependency list or install command was found in the skill, so there were no packages to look up on OSV.

Sources

Where this comes from

  • GitHubRegistry

    Checked · Days since the last commit, GitHub forks, GitHub stars, Days to a first reply on issues, Open issues, Releases in the last 90 days

A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.

Changelog

What changed

No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

Free 27-page guide

Get the free Developer’s Field Guide

A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.

Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.

No spam. Unsubscribe any time.

← Back to SkillsSubmit your own entry →