Bridge Morph, RepoPrompt, and Supermemory for cross-system search and memory-driven recall.
npx skills add https://github.com/z23cc/cc-code --skill cc-bridge
Please help me install this Agent Skill. Skill: cc-bridge Source: https://github.com/z23cc/cc-code/tree/main/skills/cc-bridge Command: npx skills add https://github.com/z23cc/cc-code --skill cc-bridge
Bridge connects Morph for fast search, RepoPrompt for structured reasoning, and Supermemory for persistent context to reduce cross-project context switching and boost review velocity.
Describe your goal to activate the bridge workflow and initiate the six-loop process for deep search, memory-enhanced chat, and cross-project review.
High-intent search queries and answers about installing and using this skill.
Persistent memory enables cross-project knowledge reuse by recalling past decisions during code reviews. You can apply previous findings and patterns to current tasks using memory-augmented reasoning across different repos.
Deep search across codebases works by combining fast search retrieval with persistent context. This memory-driven recall applies past decisions to current tasks during research-heavy workflows and cross-team reviews.
Yes, you can share reusable code patterns across different repositories and teams. The cross-team collaboration workflow connects fast search, structured reasoning, and persistent context to transfer knowledge across projects.
To reduce cross-project context switching during planning, bridge fast codebase search, structured reasoning, and persistent context. This workflow minimizes manual context retrieval and boosts review velocity.
Yes, the six feedback loops require Morph, RepoPrompt, and Supermemory integrations. These integrations enable deep search, memory-enhanced chat, review knowledge, and cross-project pattern reuse.
You should not use a bridging workflow for memory-enhanced chat if your research tasks do not require cross-system collaboration. It is strictly designed for research-heavy workflows needing deep search and cross-project pattern reuse.
laraxotSet up Supermemory infrastructure with persistent memory and semantic search.
popoffvgExtract and persist reusable insights, edits, and tasks from conversations.
as4584Combine vector and keyword search results using RRF, linear combination, or cross-encoder reranking.
Mattyreed1Conduct structured research with Perplexity AI and return cited findings.
