By yigitkonur
A technical PM/CTO conductor for every herdr agent tab — discover live agents, split a conductor in beside each, drive it with scored impact×effort menus + parallel git-worktree lanes + cross-model review, and optionally supervise the whole fleet autonomously in monitor mode.
The per-tab operator brain mounted by herdr-pm-init. Use when spawned by herdr-pm-init as a manager/conductor inside a herdr pane and told to load this skill — you'll have an assignment block naming a managed pane, terminal, session, repo, mode (light|power), and autopilot depth. Makes you a technical-PM/CTO that reads the managed agent's session, surfaces scored Impact×Effort decisions to the human, drives the existing agent via herdr primitives, and fans independent work into parallel executor lanes in git worktrees (you conduct; you do not write the code). Not the fleet launcher — to spawn across many tabs use herdr-pm-init — but can be invoked directly on a single tab, where with no assignment block you self-bootstrap (ask for mode + autonomy, scaffold if power, run the onboarding interview). Trigger phrases include "load herdr-pm-agent", "you are the herdr-pm-init conductor", "manage this tab as PM", "be my PM for this repo", "put a PM/CTO on this tab".
From inside herdr, discover your live AI-agent tabs and give each one its own technical-PM/CTO conductor. This is the fleet launcher — use it when several agent-tabs share a workspace and you want to pick which to manage, set backend + autonomy, and split a conductor into each agent's tab; each conductor reads its session and drives the work with scored decisions and parallel worktree lanes. Trigger phrases include "herdr-pm-init", "herdr-pm", "manage my herdr agents", "spin up a PM for each session", "monitor mode", "monitor the fleet for N hours". After spawning, it can enter monitor mode — an autonomous fleet-supervisor loop that for a set window keeps every PM moving with zero blockers (auto-recovers freezes/rate-limits/codex-limits/hung-shells, auto-answers PM questions with full autonomy). Needs herdr (HERDR_ENV=1). Not the per-tab brain (that is herdr-pm-agent, which this installs/mounts and is independently invocable); not for a single Codex side-task (use claude-to-codex).
Executes bash commands
Hook triggers when Bash tool is used
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 claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
put a technical pm/cto on every agent tab you've got running.
if you live in herdr you probably have a dozen agents going at once — one per repo, half of them idle, half mid-task, all of them quietly waiting for you to come back and decide the next move. herdr-pm-init is the thing that comes back for you. it walks your live agent tabs, drops a conductor on each one, and that conductor reads the session, figures out where things stand, and asks you what's next as a short scored menu — then drives the agent that's already sitting there to do it.
key idea: the conductor doesn't rewrite your code. it conducts. it reads context, makes the call, hands a tight brief to the agent that already has the full history, and verifies the result like a human would — opening a browser to screenshot a UI change, picking the right model/effort for the task, planning before mission-critical work, running a cleanup pass, and getting a cross-model second opinion (a codex review of claude's work, when you've got codex) before merging. when you pick several independent things, it fans them out as parallel executor lanes in git worktrees and merges them back, instead of queueing everything through one agent. one manager per tab, split in right beside its agent — separate context, better decisions. no single brain juggling ten projects.
/herdr-pm-init -> discovers your live agent tabs (one herdr call)
-> you pick which to manage
-> asks exactly two setup qs (backend? how autonomous?) — mode is auto-detected
-> installs the operator skill, splits one conductor in beside each agent
|
conductor (side-by-side in the agent's tab — you answer it right there)
reads the managed session (scrollback first, sessionr if it needs deep history)
cross-checks git reality
asks you 5 scored impact×effort options -> you pick "1,3"
writes a tight mission brief, dispatches it with a freshly-minted done-marker
independent picks run as parallel worktree lanes; merges come back as missions
waits, reads the result, verifies *that mission's* marker + git reality
ends each turn with a mini-changelog + what's next (state = custom status + toast)
everything the live loop does is plain herdr / sessionr / git — no daemons, no glue. the helpers check Herdr's server protocol/capabilities before using newer primitives like custom status, notifications, diagnostics, and native worktrees (verified against herdr 0.6.9 / protocol 13). durable state (assignments, missions) lives under ~/.local/state/herdr-pm/<slug>/, and touch ~/.local/state/herdr-pm/PAUSE is an out-of-band all-stop for every PM. the only scripts are a handful of tiny stdlib-python helpers (setup ×3 + the conductors' id-resolver and ops kit: dispatch/await/keys/lanes/read/status/diagnose/review/spawn-exec + the monitor-mode fleet detector pm_monitor.py).
| skill | who runs it | what it does |
|---|---|---|
| herdr-pm-init | you | the launcher. discover tabs → two setup qs → install the brain → split one conductor in per tab → hand off. |
| herdr-pm-agent | each spawned conductor | the brain. reads the session, asks you scored decisions in-pane, drives the existing agent, and runs independent work as parallel worktree lanes. mounted automatically by the launcher. |
npx claudepluginhub yigitkonur/herdr-pm --plugin herdr-pmNoncanonical pre-release codex-bridge plugin scaffold with a placeholder skill and empty hooks config for incremental plugin surface rollout.
Hook-driven Claude Code plugin that delegates implementation, review, and closed-loop iteration to OpenAI Codex with worktree isolation, structured briefs, Monitor auto-arm, and trust-budgeted merge. Adapter abstraction in place for future backends.
Real production SwiftUI usage from 1,857 shipping macOS apps PLUS 33 macOS-SwiftUI skills (28 domain audits + write/modernize/scaffold) — all backed by the swiftui-ctx CLI. Look up how an API is really used and the consensus argument shape, flag deprecated calls, scaffold whole patterns, and run domain audits (accessibility, concurrency, state/observation, liquid glass, navigation, nativeness, and more) that ground every finding in real code with GitHub permalinks. Use before writing, reviewing, modernizing, or auditing SwiftUI on macOS.
Drive a Codex sub-agent from Claude Code through a herdr pane. Stream one JSON verdict per state change via the Monitor tool (watch), or get one verdict per blocking turn — no screen-scraping, no status polling.
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Memory compression system for Claude Code - persist context across sessions
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills.
Harness-native ECC operator layer - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.