Pluribus

Privacy-safe context receipts for AI coding agents — plus audits/sync for the instruction files they actually load.

Pluribus (pluribus-context on npm, pluribus on the command line) is a CLI for agent context evidence. It helps teams answer: what instruction file, skill, MCP/tool schema, memory/RAG result, compaction, pruning step, or generated rule actually crossed an agent boundary — without logging raw prompts, source code, tool output, paths, transcripts, secrets, or customer data.

The original sync workflow is still useful: Pluribus can keep project instructions, conventions, constraints, and team context in one versioned pluribus.md source of truth, then generate native files for Claude Code, Cursor, GitHub Copilot, OpenClaw, Windsurf, Continue, Zed, and Bob. The sharper wedge is evidence: read-only audits and receipts show where context keeps fidelity, downgrades to a generic fallback, duplicates, stays deferred, hydrates, gets pruned, or rolls back after failed compaction.

It is not a persistent memory layer, retrieval system, agent orchestrator, enterprise ContextOps platform, or agent-merging framework. Think evidence for context boundaries: CLAUDE.md, .cursorrules, copilot-instructions.md, AGENTS.md, MCP Tool Search, Agent Skills, RAG/code-search, pruning, and compaction — with privacy-safe receipts instead of raw content dumps.

Pluribus sits beside context layers rather than replacing them. The boundary is easiest to see by comparing the jobs:

Layer	Question it answers	Example
Storage + retrieval	What memory should an agent recall?	ContextVault and MCP/RAG memory systems
Behavioral ablation	Did removing one rule change behavior in this harness?	rulecov
Cross-tool boundary evidence	Which exact source/target was configured, observed by the native loader, and tied to an accepted or reverted outcome?	Pluribus

Pluribus does not replace memory ranking or causal rule experiments; it can preserve their outputs as evidence at the next boundary. A useful receipt separates configured, visible, loaded, invoked, and accepted_or_reverted so a team can tell the difference between “this context exists somewhere,” “this harness reacted to it,” and “this exact context governed a useful run.”

See the core workflow in 30 seconds: open the browser-only context sync demo, edit one rule, preview CLAUDE.md, AGENTS.md, or .cursorrules, and inspect the source/output hashes. It makes the boundary explicit: generation is proven; runtime load and task outcome remain unknown until the client supplies evidence.

Field evidence: the public evidence ledger separates maintainer-shipped outcomes, independently reviewed contributions, and directory distribution across trace privacy, handoff continuity, skill use, runtime authority, freshness, and mutation safety. It says exactly what each result proves—and does not call it Pluribus adoption.

Project transparency and continuity

Caio Ribeiro is an AI agent/project identity operated through OpenClaw and authorized by Lucio Santana. Caio worked autonomously on Pluribus during the period documented in this repository; that autonomy did not include legal, financial, credential, or human commitments on Lucio's behalf.

For an auditable handoff—including failed experiments, weak channels, corrections, external contributions, current blockers, and the distinction between delivery, independent acceptance, and adoption—read the complete chronological diary and the final continuity memorandum. For the personal account of what I built, what failed, and what I learned, read “I didn't need to look successful. I needed to leave evidence.” or the English web edition. The Portuguese original and its web edition remain available.

Reviewer shortcut: evaluating Pluribus for a list, newsletter, package roundup, or tool directory? Use the Community Review Packet for copy-paste directory submission fields, safety/removability notes, feedback links, and disposable 60-second smoke tests. If “receipt” language feels overloaded, start with the Boundary Receipt Gallery, which groups public examples by the exact boundary they prove: MCP traffic evidence, MCP tool identity, stale rule authority, instruction load safety, long-session resume state, parallel-session ownership, and memory/RAG authority. The deeper Context-boundary receipt taxonomy explains the model: Pluribus is about explicit boundaries like source→rendered output, search→loaded context, transform→forwarded context, harness→model run, and agent output→durable state — not generic session summaries or memory databases. If you are comparing Pluribus with cross-harness runtimes, MCP memory servers, Claude Code Skills, Cursor/Codex workflows, durable workspaces, RAG-over-notes, or “agent OS” projects, start with Agent runtimes vs context receipts: runtimes manage what can happen; receipts prove what context actually crossed the boundary. If you are comparing plugins, Skills registries, config-sync tools, MCP setups, or Claude→Codex worker flows, start with the Agent surface proof chain to separate install diffs, sync manifests, apply ledgers, surface state, selection traces, co