Run N worker agents in parallel that drain the planning queue. Each worker loops: pull next task -> claim it (executing) -> do the work -> submit a report -> finish the task. Use when the user says "execute the plan", "run the queue", "spawn workers", or asks for parallel execution with a specific agent count.
Planning-board skill bundle for coordinating parallel coding agents with hashharness-backed append-only task, status, and report chains. Use this as the entry point to the bundled pm subskills under this directory, such as `plan`, `next`, `executing`, `report`, `finished`, `execute`, `replan`, `cancel`, `reclaim`, `sweep`, `dashboard`, `install`, `extract-steps`, and the `*-skill-execution` variants.
Cryptographic integrity attestation of a planning queue or the whole pm instance via hashharness `verify_work_package`. Re-checks every record's content hash, chain links, and schema binding across the queue's Task records plus each per-task TaskStatus / TaskReport / TaskHeartbeat chain — catching orphan records, tampered payloads, and `done` slipped in without proof. Unlike `verify_chain` (which followed a single named root), this covers every record in scope, closing the gap that pm's per-task chains have no common root. Use as a supervisor sweep before trusting a batch of agent output, or as a periodic integrity check.
Enqueue a new task on the planning board backed by hashharness. Creates an immutable Task record plus an initial TaskStatus(new). Supports subtasks (link to parent + parent's status at decision point) and dependency links to other tasks. Use when the user says "plan", "queue", "enqueue", "add task", or "create subtask".
Install the hashharness MCP backend that pm uses for its append-only storage. Bootstraps an isolated Python venv, installs hashharness from git, generates a launcher script and a source-able env file. Four install locations: ~/.hashharness/ (per-user, recommended), ~/.codex/hashharness/ (alongside Codex state), ~/.claude/hashharness/ (alongside Claude Code skills), or ./.hashharness/ (per-project at git root). Idempotent — re-running reports the existing install and exits 0. Use when a fresh workstation needs hashharness, when "pm setup" fails because no MCP server is reachable, or when you want a sandboxed second instance for testing.
Extract the major workflow steps from another skill's SKILL.md, with bash-side validation that every extracted step's anchor is verbatim in the source (catches LLM hallucination), and optional recursion into nested skill invocations (step X of skill A invoking skill B yields nested steps named `X.B.S1`, `X.B.S2`, ...). Two modes — llm (semantic, default when a supported LLM CLI is on PATH) and regex (pattern- matching fallback). Used internally by pm-auto-skill-execution, pm-assisted-skill-execution, pm-guided-skill-execution; also callable standalone for inspecting a skill's structure.
Mark a task as done (or rejected) on the planning board. Appends a terminal TaskStatus that links proof -> latest TaskReport on the task. Refuses if no TaskReport exists, enforcing "task to be finished requires proof of work/report". If the Task declares a verifier at plan time, this script runs it before allowing `done`. Use when an agent has submitted its final report and wants to close the task; pass --rejected to close as failed instead.
Drive another skill step-by-step through the planning queue, with the user in the loop at every gate. Extracts the target skill's steps from its SKILL.md, plans one task per step (chained by dependsOn), and executes them one at a time — pausing after each step to surface decisions, accept user-supplied subtask requests, and confirm before moving on. Use when the user says "guided run", "step through skill X", "drive skill X with user-in-the-loop", or asks for an execution that respects a skill's prescribed dialogue gates.