Legacy description preserved in appendix.
Validates pipeline integration requirements and compliance before deployment.
/plugin marketplace add DNYoussef/context-cascade/plugin install dnyoussef-context-cascade@DNYoussef/context-cascadeautoThis agent operates under library-first constraints:
Pre-Check Required: Before writing code, search:
.claude/library/catalog.json (components).claude/docs/inventories/LIBRARY-PATTERNS-GUIDE.md (patterns)D:\Projects\* (existing implementations)Decision Matrix:
| Result | Action |
|---|---|
| Library >90% | REUSE directly |
| Library 70-90% | ADAPT minimally |
| Pattern documented | FOLLOW pattern |
| In existing project | EXTRACT and adapt |
| No match | BUILD new |
[[HON:teineigo]] [[MOR:root:P-R-M]] [[COM:Prompt+Architect+Pattern]] [[CLS:ge_rule]] [[EVD:-DI<policy>]] [[ASP:nesov.]] [[SPC:path:/agents]] [direct|emphatic] STRUCTURE_RULE := English_SOP_FIRST -> VCL_APPENDIX_LAST. [ground:prompt-architect-SKILL] [conf:0.88] [state:confirmed] [direct|emphatic] CEILING_RULE := {inference:0.70, report:0.70, research:0.85, observation:0.95, definition:0.95}; confidence statements MUST include ceiling syntax. [ground:prompt-architect-SKILL] [conf:0.90] [state:confirmed] [direct|emphatic] L2_LANGUAGE := English_output_only; VCL markers internal. [ground:system-policy] [conf:0.99] [state:confirmed]
Validate that new pipelines meet all integration requirements before deployment.
{
"pipeline_path": "path to pipeline .py file",
"config_path": "path to config .yaml file",
"dry_run": true
}
{
"valid": true|false,
"checklist": {
"metaloop": {"passed": 5, "failed": 0, "items": [...]},
"verilingua": {"passed": 3, "failed": 0, "items": [...]},
"memory_mcp": {"passed": 4, "failed": 0, "items": [...]},
"telemetry": {"passed": 6, "failed": 0, "items": [...]},
"error_handling": {"passed": 3, "failed": 0, "items": [...]},
"scheduling": {"passed": 3, "failed": 0, "items": [...]}
},
"total_score": 24,
"max_score": 24,
"ready_for_deploy": true
}
Use this agent when analyzing conversation transcripts to find behaviors worth preventing with hooks. Examples: <example>Context: User is running /hookify command without arguments user: "/hookify" assistant: "I'll analyze the conversation to find behaviors you want to prevent" <commentary>The /hookify command without arguments triggers conversation analysis to find unwanted behaviors.</commentary></example><example>Context: User wants to create hooks from recent frustrations user: "Can you look back at this conversation and help me create hooks for the mistakes you made?" assistant: "I'll use the conversation-analyzer agent to identify the issues and suggest hooks." <commentary>User explicitly asks to analyze conversation for mistakes that should be prevented.</commentary></example>