BigHugger
sk Skill · affaan-m

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing…

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A diagnostic skill that audits agent and LLM applications across a 12-layer stack, checking for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. It produces severity-ranked findings with code-first fixes through a four-phase workflow of scoping, evidence collection, failure mapping, and fix strategy.

Reach for it when an agent or LLM feature misbehaves and you don't know which layer is failing, or before shipping an agent stack.

Use it to

  • Diagnose an agent feature whose failing layer is unknown
  • Audit an agent stack before production release
  • Trace memory contamination across conversations
  • Verify tool declarations are enforced in code
  • Rule out wrapper-layer regression before blaming the model

For Developers building agent applications, autonomous loops, or LLM features

Host repository
affaan-m/ECC
Installs, lifetime
3,100
Installs, 8 weeks
1,824
Allowed tools
Read, Write, Edit, Bash, Grep, Glob
Host stars
259k
Host language
JavaScript
topicsagentsllmdebuggingauditdiagnosticsarchitecture