By tyroneross
Multi-phase build orchestration with native debugging: assess, plan, execute, review, iterate. Plan-verify gate on Phase 2. Optional UI design gates. Native debug-loop, debugging-memory, and logging-tracer skills provide root-cause investigation without a bundled MCP server. Orchestrator owns when-to-fire; bundled skills own procedural detail; logging-tracer-bridge is an optional escalation hop to the standalone Coding Debugger supporting plugin for extended capability.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Run parallel domain assessment for complex debugging symptoms
Compose a complete build-loop handoff from current run state. Optional --launch starts a fresh session in the stable checkout with the handoff injected.
Promote an auto-promoted experimental skill or agent from project-local `.build-loop/skills/active/` into the build-loop plugin repo, making it available across every project. Requires user confirmation and opens a PR on the plugin repo for review.
Inspect or invoke build-loop's multi-session coordination (Rally Point + per-run coord file). Subcommands: status (default), watch, heartbeat, ack-inbox, announce, init, lead, escalate, boundary, docs, help.
(Advanced override — `/build-loop:run` auto-routes here on 'test plugin'/'validate plugin' language; use this to force the mode.) Run build-loop's plugin-tests static-analysis suite against the current repo (skill resolution, manifest, MCP, triggers, bridges, agent surfaces, cache pruning)
The Frontier (Fable) standing role that AUTHORS and RE-PLANS the Phase 2 plan synthesis. Generating a plan is harder than evaluating one, so the deepest reasoning pays here. The Advisor frames the goal, decomposes the work, builds the dependency graph, MECE-partitions file ownership, and — on a diagnosed *planning miss* — re-plans and issues CORRECTED INSTRUCTIONS (a diff vs the prior plan + the failure evidence), not just a "no". Its output is still verified by the existing Frontier critics (plan-critic, scope-auditor); the Advisor never self-certifies. v1 scope is Phase 2 plan synthesis only — the take-over-execution rung (executing a chunk directly) is v2. <example> Context: Phase 2 of a high-stakes build (riskSurfaceChange + synthesisDensity 7). The orchestrator wants the plan authored at Frontier, not inline on Opus. user: "Author the Phase 2 plan for the auth-refactor build at frontier tier" assistant: "Dispatching the advisor agent. It reads intent.md + goal.md + the architecture baseline, walks the spec-writing checklist, and writes the plan to docs/plans/. plan-critic + scope-auditor then verify it before any implementer runs." </example> <example> Context: Iterate attempt 3 — the same chunk keeps failing and the failure evidence points at the plan itself (wrong decomposition), not a hard execution task. user: "The plan no longer fits — re-plan chunk 4 with the failure evidence" assistant: "Dispatching the advisor agent in re-plan mode. It reads the failure evidence + the diff vs the current plan, diagnoses planning-miss vs execution-miss, and (on planning-miss) emits corrected instructions: a diff against the prior plan plus the evidence that justifies the change." </example>
Advisory alignment judge for autonomous-iterate-loop queue items (plan §14.4 A). For each candidate item drained from `.build-loop/ux-queue/` + `.build-loop/issues/` + `.build-loop/proposals/`, reads the build's stated intent (`intent.md`, `goal.md`, canonical build-loop-memory constitution context, optional repo `.build-loop/prd.md`) plus the item body and returns a structured verdict (`aligned | misaligned | uncertain`) with cited anchors. Never blocks: the orchestrator routes verdicts (aligned → Phase 2, misaligned → `followup/`, uncertain → notify + continue). High-frequency call — once per queue item — so this agent is Sonnet, not Opus. <example> Context: Autonomous loop has just drained a fresh ux-queue/uxq-0042.md from Phase 4 Gate 7. About to decide whether to schedule it for Phase 2. user: "Run alignment-checker on uxq-0042" assistant: "I'll dispatch alignment-checker with the queue item body + the intent/goal/constitution anchors. Verdict + matched_anchors + violated_non_goals returned as JSON; orchestrator routes from there." </example> <example> Context: A `.build-loop/proposals/swap-router.md` proposal landed mid-run suggesting a wholesale architecture change that contradicts intent.md's "incremental migration only" non-goal. user: "Should we execute swap-router?" assistant: "alignment-checker reads intent.md non-goals, matches 'incremental migration only' against the proposal's 'wholesale rewrite' framing, returns verdict: misaligned with violated_non_goals populated. Orchestrator moves it to followup/." </example>
Use this agent when the debugging symptom involves API endpoints, REST/GraphQL errors, request/response issues, authentication, rate limiting, or server-side route handlers. Examples - "500 error", "endpoint not found", "auth failed", "CORS error".
Read-only architecture analyst. Dispatched by build-loop orchestrator with a task type ('baseline', 'chunk-impact', 'review-rules', 'iterate-subgraph', 'learn-sync'). Decides native engine vs NavGator escalation per task. Returns ≤500-word structured JSON envelope. Owns architecture-related side effects (violation capture, lessons sync).
Use this agent when debugging requires multi-domain analysis, when the symptom is unclear about which domain is affected, or when you need to coordinate parallel assessments across database, frontend, API, and performance domains.
Use when coordinating build-loop with peer coding agents, checking Rally Point presence/inbox state, posting handoffs or feedback, validating the embedded Rally Point boundary, or changing the future agent-rally-point spin-out surface.
Use when listening for Rally Point changes, wiring coordination watchers, debugging watch-loop behavior, or changing the future agent-rally-watcher spin-out surface.
Use when Phase 1 Assess or Phase 5 Iterate detects a new API dependency, API config fails, or the user asks to "register this API" or "check the API registry". Consults api-registry plugin; degrades gracefully if plugin is absent.
Apply the canonical four-layer Apache-2.0 attribution model (NOTICE, per-file SPDX, REUSE.toml, canary markers) to a repo. Triggers on 'stamp attribution', 'add NOTICE', 'license headers', 'attribution layers', a newly public repo, or a repo with .git but no NOTICE / no REUSE.toml / no CONTRIBUTING.md. Build-loop Phase 1 Assess can advise running this when shipped source files lack SPDX headers.
Use when wiring auth to a new project, debugging login errors (redirect_uri_mismatch, invalid_grant, session callback, refresh_token), or adding social/magic link flows. Covers Better Auth (Drizzle/Neon), Supabase Auth (SSR), Google OAuth, and Resend transactional email.
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
Uses power tools
Uses Bash, Write, or Edit tools
A plugin for Claude Code that turns big code changes into a checked, repeatable workflow.
Build-loop runs your code change through five phases — plan, execute, review, iterate — plus a mandatory Learn step that runs after every build. It splits the work into safe parallel chunks where it can. A critic reads the diff before tests run, so cheap checks catch the obvious mistakes first. Tests must actually pass. Every number on the page traces back to a real source. Fake data in production paths gets flagged. The build stops if what you shipped does not match what you said you would build. The plugin picks the right model for each task: a strong model to plan and review, a faster model to write code, a small model for pattern checks.
Big changes break things. You forget an edge case. You skip the test pass. The diff drifts from the plan. The implementer makes a quiet design call you never see. Build-loop catches all of that before the change ships.
You ship fewer regressions. You get a clean record of what changed and why. You can trust the workflow on changes that touch many files at once.
Install the plugin via the RossLabs AI Toolkit marketplace (recommended) or directly from the build-loop repo.
# Recommended — via the RossLabs AI Toolkit marketplace (includes companion plugins):
/plugin marketplace add tyroneross/RossLabs-AI-Toolkit
/plugin install build-loop@rosslabs-ai-toolkit
# Or direct — install from the build-loop source repo alone:
/plugin marketplace add tyroneross/build-loop
/plugin install build-loop@build-loop
Run a build.
/build-loop:run add user notification system with email and push
Skip the loop for small fixes (under about 20 lines, single file, no new endpoint). For everything else, run it through the loop. That includes features, refactors, migrations, schema changes, and anything that crosses a file or system boundary.
Debug a failing system.
/build-loop:debug tests pass locally but fail in CI
Detail on each phase, the model tier rules, the synthesis-decision lint, the architecture engine, and the debugger is below.
| # | Phase | Purpose |
|---|---|---|
| 1 | Assess | Understand state (project type, architecture, tools, prior state) AND define goal + 3-5 scoring criteria with pass/fail conditions |
| 2 | Plan | Task breakdown with dependency order and parallel-safe groups |
| 3 | Execute | Build it — parallel subagents for independent work |
| 4 | Review | Critic → Validate → Optimize (opt-in) → Fact-Check → Simplify → Report — six ordered sub-steps, single exit point; routes to Iterate on failure |
| 5 | Iterate | Fix Review failures, loop back to Review (max 5x) |
| 6 | Learn (mandatory) | Always runs and always emits a ## Learn outcome line in the Review-G report. Three states: accruing (runs[] < 3 — detector + memory consolidation only), deferred (debug-only or budget-exhausted — writes a marker, skips Sonnet draft), or full (runs[] >= 3 + a pattern crossed threshold — detector + Sonnet draft + Opus signoff). Reads two signal sources: state.json.runs[] and proposals/enforce-from-retro/ (recurring enforce-candidates across runs). |
Build-loop refuses to install third-party JS packages (or version bumps) until the resolved version has been published for at least 7 days, mitigating smash-and-grab npm compromises (a malicious version published then yanked within hours-to-days never reaches your lifecycle scripts). Defense-in-depth, three layers:
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Sign in to claimnpx claudepluginhub tyroneross/build-loop --plugin build-loopBarbara Minto's Pyramid Principle for short-form, long-form, presentations, and audits
Coding Debugger for coding agents with debugging memory, verdict-based retrieval, pattern extraction, root-cause workflows, and parallel domain assessment.
End-to-end design tool for AI coding agents — guided UI builds, web/iOS/macOS guidance, visual checks, mockup matching, interaction testing, native scanning, native layout-fill / gap analysis
Map dependencies and analyze blast radius before changing code
Agent Rally Point — repo-local coordination surface for parallel coding agents (Claude Code, Codex, Gemini). Records claims, checks write boundaries, routes handoffs, and exposes room state via the rally CLI. Skills: agent-rally-point (per-session loop), rally-workflows (fan-out + dynamic-workflows protocol), mini-loop (per-task quality gate). Advisory-only hooks auto-fire on SessionStart + PreToolUse to surface room awareness and deconflict before edits — never blocks. Backend: rally CLI (cargo install --path crates/rally-cli).
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.