aiwg
Reusable project context and specialist workflows for the AI tools you already use. Agents, skills, rules and MCP tools for Claude Code, Codex, Copilot, Cursor and more, plus SDLC workflows, session memory, and Jev decision support that offloads bounded LLM decisions to save tokens.
Not yet testedsource: GitHubhomepageTypeScriptMITcommit 21935112bc57
TypeScript, MIT licensed. The project labels itself: agent skills, agentic ai, ai agents, claude code, codex, coding agents, context engineering and copilot.
aiwg has not been verified yet.
Measured by Argusic on a fresh machine every time. Every number links to its evidence.
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
No recorded runs.
Topics (from GitHub)
agent-skillsagentic-aiai-agentsclaude-codecodexcoding-agentscontext-engineeringcopilotcursordecision-enginedecision-supportdeveloper-toolsjevllmmcpmulti-agentprompt-engineeringsdlctoken-optimizationworkflow-automation
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Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/aiwg)Questions
- Does aiwg run?
- aiwg has not been fully verified yet. No recorded run has produced a verdict yet.
- How did Argusic test aiwg?
- On a fresh, disposable machine, with every command recorded. 0 attempts are recorded, and the full method is on the methodology page.
- Where is the evidence for aiwg?
- All 0 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.