Model-agnostic, hook-level behavioral enforcement engine for AI coding agents. Deploys onto any model using cli-wikia's per-model knowledge.
Project description
CLI Enforcement
Model-agnostic, hook-level behavioral enforcement for AI coding agents. The enforcement engine (state manager, points/tiers, anti-hallucination, sandbox, cascade) is platform-neutral; where and how it installs onto a given model is supplied dynamically by cli-wikia — so one engine deploys onto Claude, Gemini, Copilot, DeepSeek, Antigravity, … with no per-platform template.
How it works
cli-enforcement deploy <model>
│
├─ asks cli-wikia: config_root? hook_events? instruction_file?
│
├─ maps enforcement STAGES (pre-tool, post-tool, stop, …)
│ to that model's REAL event names (PreToolUse / BeforeTool / …)
│
└─ copies the engine into <config_root>/mcp/ and writes the hook registry
Install
pip install cli-enforcement # pulls in cli-wikia
Usage
cli-enforcement deploy claude # dry-run: show the plan
cli-enforcement deploy claude --write # actually install into ./.claude/
cli-enforcement deploy gemini --write # same engine, wired to Gemini's events
cli-enforcement status # scorecard: points, tier, streak, KB gates, failures
cli-enforcement status --json # same data, machine-readable (used by cli-fleet dashboard)
cli-enforcement remove claude --write # remove the engine
Dry-run by default — nothing is written without --write.
License
MIT — see LICENSE.
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