By mistakeknot
Work prioritization and next-task analysis for Claude Code — tradeoff-aware recommendations from project state.
Work prioritization for Claude Code.
internext reads your project's beads state and recommends what to work on next. Not a neutral menu of options: an opinionated recommendation with explicit tradeoff analysis.
Each candidate gets scored on three axes: impact (does it unblock other work? does it build capability?), effort (30 minutes or multi-session?), and risk (mechanical task or rabbit hole?). Items that block other items get an impact bonus: a P2 that unblocks three P1s is worth more than a standalone P1.
There's a built-in completion bias: finishing in-progress work almost always beats starting new work, because the switching cost of abandoned context is real and consistently underestimated.
First, add the interagency marketplace (one-time setup):
/plugin marketplace add mistakeknot/interagency-marketplace
Then install the plugin:
/plugin install internext
/internext:next-work
Or ask naturally:
"what should I work on next?"
"prioritize my backlog for this session"
The skill reads from bd ready, bd list, and bd stats to build its picture of the project state, then delivers 3-5 scored options with a clear recommendation.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claim[DEPRECATED — use intervox] Analyze your writing style and adapt Claude's output to sound like you. Replaced by intervox (via the interim intervoice), which adds a measured stylometric fingerprint, LLMism linter, and verified closed-loop apply on top of the global multi-register profile.
Self-improving agent rig: codifies product and engineering discipline into composable workflows from brainstorm to ship. Compounds knowledge, generates domain agents, monitors its own docs, and surfaces conservative update drift. Orchestrates Claude, Codex, and Oracle through 6 agents, 57 commands, 20 skills, 0 MCP servers. Factory substrate: CXDB turn DAG, scenario bank with satisfaction scoring, evidence pipeline, agent capability policies. Companions: interspect, interphase, interline, interflux, interpath, interwatch, interslack, interform, intercraft, interdev, interpeer, intertest.
Recursive AGENTS.md generator with integrated Oracle critique, CLAUDE.md harmonization, incremental updates, diff previews, and smart monorepo scoping. Cross-AI compatible.
Token efficiency benchmarking, session analytics, and API-equivalent cost analysis for agent workflows
Multi-agent review and research with scored triage, domain detection, content slicing, intermediate finding sharing, and knowledge injection. 17 agents (12 review + 5 research), 8 commands (incl. flux-melange — a goal-seeking adaptive review loop with lens fusion and novelty/risk/taste scoring), 3 skills (flux-engine, flux-review-engine, flux-melange-engine), 2 MCP servers (exa, openrouter-dispatch). Companion plugin for Clavain.
npx claudepluginhub mistakeknot/interagency-marketplace --plugin internextAI-supervised issue tracker for coding workflows. Manage tasks, discover work, and maintain context with simple CLI commands.
Sprint planning with story prioritization and capacity estimation
Convert design documents, PRDs, and task lists into beads issues with lossless conversion, proper epic hierarchy, validated dependencies, and three independent subagent review passes.
Configure Claude Code to track work using Beans.
Plan-only mode and GitHub-issue-to-Beads workflow. Provides planning without auto-execution and structured work decomposition into Beads epics, tasks, and sub-tasks with verifiable acceptance criteria.
Ultra-compressed communication mode. Cuts 65% of output tokens (measured) while keeping full technical accuracy by speaking like a caveman.