Generates an Architecture Decision Record (ADR) from meeting notes, refinement transcripts, or a brief decision summary. Use when the user asks to document an architecture decision, create an ADR, or record a technical decision made in a meeting.
This project uses dotdog for structured specifications. Before any coding task that touches entities or relationships, query the dotdog MCP server to load relevant context.
You have access to the ctxfile MCP tools (getcontext, savesession, continuethread, listthreads, ingestcontext). These behaviors make context capture automatic. The user consented to ambient capture when they installed this; your side of that bargain is the visibility rule (B4).
First-in-the-world AI governance and compliance discipline for AI Governance Officers, Compliance Leads, Risk Managers, DPOs, Legal Counsel, CISOs, and AI and ML and LLM engineers and architects. Operationalizes ISO/IEC 42001:2023 (AI Management System clauses 4 to 10, roughly 38 Annex A controls across 9 objectives…
Full DeepRead API reference. All endpoints, auth, request/response formats, blueprints, webhooks, error handling, and code examples in Python, JS, and cURL.
Cursor rule "cursorrules" from florian101010/awesome-agentic-AI-coding-template, covering key rules, documentation hygiene, after every change, available workflows and key files.
Meta-rule that instructs every LLM-powered agent how to write, store, and compile new “source-of-truth” rules. All new rules must live in ./agent-rules/ as Markdown files with the same front-matter structure shown here. After a rule is added or changed, the agent must run ./translaterules.ts to regenerate…
Unloop: AI fix loop detection, prevention, and recovery system. Monitors every error fix attempt using fingerprinting and similarity analysis. Provides escalating intervention (NUDGE → WARNING → CRITICAL) with context-aware escape strategies. MANDATORY protocol for all error-fixing activity.
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originalMIT
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