Plan Orchestrate
Execute all tasks in a plan using parallel TDD workers. Fully autonomous after invocation.
Usage
plan-orchestrate {plan-name}
Example: plan-orchestrate user-auth
Prerequisites
First, resolve the plans directory, once, and reuse $PLANS_DIR for every path below. It is .claude/plans unless the project overrides it in .claude/hcf.json (see Plans Directory in the README). The script answers with an absolute path resolved from the project root, so the result does not depend on the working directory:
PLANS_DIR="$("{skill-base-dir}/../../hooks/resolve-plans-dir.sh")" || exit 1
Never substitute a hand-written jq line or a literal .claude/plans. A non-zero exit means the project root or the configured value is unusable; surface the script's stderr verbatim and stop. Quote every path built from $PLANS_DIR — a configured directory may contain spaces.
Then:
- Plan must exist at
$PLANS_DIR/{plan-name}/ - Project must be configured (
.claude/testing.mdexists) - Plan status must be
readyorin_progress
Check prerequisites:
ls "$PLANS_DIR/{plan-name}/_plan.md" .claude/testing.md 2>/dev/null
If not found, output error and stop.
- Must be on the correct feature branch
Verify the current branch matches feature/{plan-name}:
git branch --show-current
If the current branch is not feature/{plan-name}:
- Output an error explaining which branch is expected
- Ask the user if they'd like to check out
feature/{plan-name} - Do NOT proceed until on the correct branch
Project Configuration
Execution Algorithm
Step 0: Suggest Unattended Completion via /goal
Claude Code's built-in /goal command keeps a session working toward a
verifiable end state — its evaluator runs after each turn and pushes execution
to continue until the condition is met. Only the user can set a goal (/goal
is a user-typed command and cannot be invoked from a skill), so surface a
copy-pasteable tip and continue immediately. This is informational, never a
gate — do not wait for a response.
Display:
Tip: for large plans, you can keep this run going unattended with Claude Code's
built-in /goal command (interrupt me now to set it, or set it before a future run):
/goal the {plan-name} plan run reached a terminal state: plan-orchestrate output ALL_TASKS_COMPLETE or TASKS_BLOCKED
Either way, an interrupted run resumes from disk — just re-run plan-orchestrate {plan-name}.
The suggested condition deliberately names both terminal outputs. A goal
phrased as only ALL_TASKS_COMPLETE leaves the evaluator demanding more turns
after a legitimately blocked run, when the correct behavior is to stop and
report the blockage.
Step 1: Load Plan Context
Read plan files:
$PLANS_DIR/{plan-name}/_plan.md- Plan overview$PLANS_DIR/{plan-name}/*.md- All task files (excluding _plan.md)
Note: Testing and code standards are auto-included above.
Parse each task file to extract:
- Task number (from filename)
- Status (pending | in_progress | completed | blocked)
- Dependencies (from
Depends onfield) - Requirements (checkboxes)
- Retry count
Build a dependency graph as a data structure.
Step 2: Update Plan Status
If plan status is ready, change to in_progress:
- Edit
$PLANS_DIR/{plan-name}/_plan.md - Set
## Statustoin_progress
Establish the run fingerprint. Every hook call below passes this back via
--expect=, so that agent files changing mid-run halt the orchestration rather
than silently swapping the pipeline. Read
$PLANS_DIR/{plan-name}/.hook-fingerprint and handle three distinct states —
conflating them is the mistake to avoid:
| State | Action |
|---|---|
Present and parseable (one line: discover-hooks-fingerprint-v1 <64-hex>) |
Use it as $RUN_FINGERPRINT. Pass the file's contents verbatim — do not trim, reformat, or re-derive them. |
| Missing | Not an error. Plans created before this feature have none. Capture one and write it to the plan directory so a resumed run is covered too, then continue: "{skill-base-dir}/../../hooks/discover-hooks.sh" --fingerprint > "$PLANS_DIR/{plan-name}/.hook-fingerprint" |
| Present but unparseable (empty, truncated, prose, wrong length) | Halt. Do not silently recapture — that would mask a botched write. Tell the user to delete the file to re-baseline. |
Never reconstruct, abbreviate, or recall a fingerprint from memory. It is only ever produced by running the script. A hallucinated digest fails every subsequent hook with bogus drift and bricks the run.
Step 2a: Pre-Implementation Hook
Run the pre-implementation hook once, after the status is set to
in_progress and before the first batch is spawned.
Resolve and run enrolled agents via the HOOKS.md discovery routine (see
Hook Discovery below) with HOOK = pre-implementation. Pass
each agent the project context as described in
Spawning hook agents.
Exit 0 with empty stdout is an empty hook: return immediately, log nothing, do no work, and proceed to Step 3. Any non-zero exit stops the run — see Hook Discovery for the full result table.
Step 3: Find Ready Tasks
A task is ready when:
- Status is
pending - ALL dependencies have status
completed
ready_tasks = []
for each task in tasks:
if task.status == "pending":
if all(dep.status == "completed" for dep in task.dependencies):
ready_tasks.append(task)
Step 4: Check Termination Conditions
All Complete:
if all(task.status == "completed" for task in tasks):
Run Step 4a: End-of-Run Hooks (quality gates + commit sequence before final completion)
STOP
Blocked State:
if len(ready_tasks) == 0:
if any(task.status == "pending" for task in tasks):
# Tasks exist but none are ready - dependency deadlock or all blocked
blocked_tasks = [t for t in tasks if t.status == "blocked"]
Output: TASKS_BLOCKED: {list blocked task numbers and reasons}
STOP
Hook Discovery
All hooks in this skill (pre-implementation, pre-batch, post-batch,
post-implementation, pre-commit, post-commit) resolve their enrolled
agents by running hooks/discover-hooks.sh, the single implementation of
HOOKS.md → Discovery Routine. Never
enumerate agent files by hand and never write a glob loop to do it. For a
given HOOK:
"{skill-base-dir}/../../hooks/discover-hooks.sh" --hook=<HOOK> --expect="$RUN_FINGERPRINT"
{skill-base-dir} is the Base directory for this skill value stated when
this skill loaded — it is given verbatim, so no path inference is needed.
${CLAUDE_PLUGIN_ROOT} is not available in a skill's Bash calls.
$RUN_FINGERPRINT is the value established at Step 2.
Then, by result:
- Exit 0, empty stdout → empty hook. Return immediately — no staging, no diffing, no spawns, and no logging or narration. "No narration" is literal and is the rule most often broken: do not name the hook, do not say it is empty/skipped, do not explain why it is empty, and do not say the discovery script returned no agents. A filtered query prints zero bytes precisely so there is nothing to echo. An empty hook is completely invisible in the user-facing output. See HOOKS.md → Empty-hook fast path.
- Exit 0, output → PRINT it verbatim as the resolved order, then spawn.
- Exit 1 or 2 → stop the run. Surface stderr verbatim.
- Exit 3 → stop the run. An agent file declares an invalid
phaseormode. Surface stderr verbatim; it names the file and the fix. - Exit 4 → halt HCF. Hook enrollment changed since this run started, so the remaining hooks would execute a different pipeline than the plan was reviewed against. Surface stderr verbatim. Do not continue the batch loop and do not commit.
- Script missing or not executable → hard failure. Say so and stop. There is no prose fallback; reconstructing the routine by hand is the failure this design exists to end.
Only exit 0 with empty stdout is an empty hook. Every other non-zero exit is an error to report loudly.
On a normal (exit 0, non-empty) result, spawn each agent per its mode field
(single → one subagent for the whole plan; batch → split the relevant file
list into batches of ~10 and spawn parallel subagents, one Task call per
batch, all in a single message). The spawn mode comes from the agent's mode
frontmatter field — never from sniffing the agent body text.
Spawning hook agents
Hook agents are spawned with the Task tool using subagent_type="{agent-name}".
The orchestrator only has <testing> and <code-standards> in context (see
Project Configuration) — it does NOT have
<architecture>. Pass each hook agent the project context it needs verbatim:
CRITICAL: Pass the COMPLETE, VERBATIM content of the
<code-standards>and<testing>tags above. Do NOT summarize, condense, or paraphrase. The full documents contain nuanced rules that are lost when summarized. Copy-paste the entire content between the tags.
For a batch agent, send one prompt per batch:
## Code Standards
{paste the COMPLETE content of <code-standards> verbatim — do NOT summarize}
## Testing Standards
{paste the COMPLETE content of <testing> verbatim — do NOT summarize}
## Files to Review
{list of files in this batch, one per line}
For a single agent, send one prompt covering the whole plan, including the
plan name, the changed-files list, and <testing> + <code-standards> verbatim.
If a hook agent needs project architecture, that is out of scope for this orchestrator — it does not load
<architecture>. Do NOT fabricate an## Project Architecturepaste here.
Step 4a: End-of-Run Hooks (Post-Implementation → Tests → Commit)
When all tasks are complete, run the end-of-run hook sequence. The control flow is strictly:
post-implementation → run full test suite → pre-commit → commit → post-commit
CRITICAL INVARIANT: NOTHING is committed until AFTER the full test suite passes. This ensures no broken code is ever committed. The
pre-commithook runs after tests pass and before the commit;post-commitruns after the commit and before the push/PR prompt.
1. Run the post-implementation hook:
Resolve and run enrolled agents via the Hook Discovery
routine with HOOK = post-implementation. To give batch agents a file list,
first compute the changed files (this stages everything only to read the list,
then unstages — nothing is committed):
git add -A && git diff --name-only --cached && git reset HEAD
Then spawn the resolved agents per their mode (see
Spawning hook agents). Exit 0 with empty stdout is
an empty hook: return immediately, no logging, no work, and proceed to step 2.
Any non-zero exit stops the run — see Hook Discovery.
2. After ALL post-implementation agents complete, run validation:
# Run full test suite
{parallel test command from testing.md}
CRITICAL: Nothing is committed until AFTER the full test suite passes. This ensures no broken code is ever committed.
3. On test failure — isolate the cause (see
Test-failure isolation below), then either commit the
implementation only or output TASKS_BLOCKED.
4. On tests passing — run the pre-commit hook:
Resolve and run enrolled agents via Hook Discovery with
HOOK = pre-commit. These run after the suite passes and before the commit.
Exit 0 with empty stdout is an empty hook (silent no-op); any non-zero
exit stops the run before the commit — see Hook Discovery.
If a
pre-commitagent modifies files, those edits are part of this commit. A pre-commit agent that changes files could break tests; that risk is covered by the Test-failure isolation stash, which now spans both post-implementation and pre-commit hook output.
5. Commit:
First, update _plan.md status to completed. Then stage and commit everything together in a single commit:
# 1. Update plan status BEFORE committing
# (edit $PLANS_DIR/{plan-name}/_plan.md — set Status to "completed")
# 2. Stage everything: implementation + hook agent fixes + plan files (including updated status)
git add -A "$PLANS_DIR/{plan-name}/"
git add -A
git commit -m "feat({plan-name}): {plan title summary}"
IMPORTANT: There must be exactly ONE commit here — do NOT make a separate commit for the plan status update. Update the status first, then stage and commit all changes together.
6. After the commit succeeds — run the post-commit hook:
Resolve and run enrolled agents via Hook Discovery with
HOOK = post-commit. These run after the commit and before the push/PR
prompt (the Output Summary at the end of this skill).
Exit 0 with empty stdout is an empty hook (silent no-op); any non-zero
exit is reported loudly — see Hook Discovery. The commit
has already happened, so report the failure rather than trying to undo it.
post-commitagents that produce uncommitted changes are REPORTED, not silently committed. The commit above already happened; do not amend or create a second commit. Surface any working-tree changes a post-commit agent left behind so the user can decide what to do.
Output: ALL_TASKS_COMPLETE
Test-failure isolation
If the full test suite fails at step 3 (or after pre-commit edits), isolate
whether the hook agents (any post-implementation or pre-commit agent
that edited files) broke things versus the implementation itself. The git stash
isolation spans both the post-implementation and pre-commit hook output:
git stash
Re-run the test suite on just the implementation.
- If implementation tests pass: a hook agent (post-implementation or pre-commit)
broke something. Drop the stash, commit implementation only, and output:
ALL_TASKS_COMPLETE WARNING: A post-implementation or pre-commit hook agent broke tests. Implementation committed without hook fixes. Review and run manually. - If implementation tests also fail: a TDD worker produced broken code. Restore
the stash (
git stash pop) and outputTASKS_BLOCKEDwith details.
Step 5: Spawn Parallel Workers
Pre-batch hook (this loop iteration). Before spawning workers, run the
pre-batch hook via the Hook Discovery routine with
HOOK = pre-batch. Because this runs on every loop iteration, honoring the
empty-hook fast no-op is important: on exit 0 with empty stdout, return
immediately — log nothing, do no work — so unconfigured loops add zero overhead.
Any non-zero exit stops the run; per-iteration checking is also what makes
drift (exit 4) surface promptly rather than at the end. See
Hook Discovery.
For EACH ready task, spawn a Task tool subagent in parallel (single message with multiple Task tool calls):
Use the Task tool with subagent_type="tdd-worker" for EACH ready task.
All Task tool calls MUST be made in a SINGLE message to enable parallel execution.
Worker Prompt (pass to each tdd-worker):
CRITICAL: Pass the COMPLETE, VERBATIM content of the
<testing>and<code-standards>tags above. Do NOT summarize. Subagents have no access to CLAUDE.md or project files beyond what you provide.
## Task File Path
{the concrete resolved path, e.g. $PLANS_DIR/{plan-name}/{task-file}.md}
## Project Testing Configuration
{paste the COMPLETE content of <testing> verbatim — do NOT summarize}
## Code Standards
{paste the COMPLETE content of <code-standards> verbatim — do NOT summarize}
## Your Task
{contents of the task file}
The tdd-worker agent already has all TDD methodology and rules. The prompt needs the project-specific configuration and task details since subagents do not inherit CLAUDE.md context.
Pass the concrete path under ## Task File Path, not the literal $PLANS_DIR — the worker marks checkboxes and appends implementation notes there, and it must never read .claude/hcf.json or assume a default to find it. One resolver runs in this skill; every subagent is handed a finished path.
Step 6: Collect Results
Wait for ALL parallel Task tool calls to complete. For each result:
On TASK_COMPLETE:
- Verify all requirements are checked in task file
- Set task status to
completed - Update the task table in
_plan.md
NOTE: Do NOT commit here. All commits are deferred to Step 4a, after standards enforcement and the full test suite pass. This ensures no non-standard code is ever committed.
On TASK_FAILED:
- Increment retry count in task file
- If retry count >= 3:
- Set status to
blocked - Set blocked reason from error message
- Update task table in
_plan.md
- Set status to
- If retry count < 3:
- Keep status as
pending(will retry in next batch) - Log the failure for visibility
- Keep status as
Post-batch hook (this loop iteration). After all results for this batch are
collected and statuses are updated, run the post-batch hook via the
Hook Discovery routine with HOOK = post-batch. Any
non-zero exit stops the run. Because this
runs on every loop iteration, honoring the empty-hook fast no-op is
important: if no agents are enrolled, return immediately — log nothing, do no
work — so unconfigured loops add zero overhead.
Step 7: Report Progress
After processing the batch, output:
Batch complete:
Completed: {list of completed task numbers}
Failed (will retry): {list of failed tasks with retry < 3}
Blocked: {list of newly blocked tasks}
Progress: {completed}/{total} tasks
Ready for next batch: {count of newly ready tasks}
Step 8: Continue Loop
Return to Step 3 and find the next batch of ready tasks.
Continue until:
ALL_TASKS_COMPLETE- All tasks finished successfullyTASKS_BLOCKED: [list]- No progress possible
Handling Edge Cases
Task Already In Progress
If a task has status in_progress (from interrupted previous run):
- Treat it as
pendingand include in ready check - The worker will pick up where it left off based on [x] marks
Partial Completion
If some requirements are already [x] in a task:
- Worker will skip those and continue with unchecked ones
- This enables resumption after interruption
Dependency on Blocked Task
If task A depends on blocked task B:
- Task A can never become ready
- It should be reported in final TASKS_BLOCKED output
Test Failures in Completed Requirements
If a previously passing test starts failing:
- Worker should report TASK_FAILED
- Investigation needed - likely a breaking change
Session Persistence
Session persistence is native to Claude Code — no plugin is required:
- Context limits are not a failure mode. When the conversation grows long, auto-compaction summarizes it and execution continues.
- All run state lives on disk. Task statuses, requirement checkboxes, and
retry counts are stored in the plan files, so re-running
plan-orchestrate {plan-name}resumes exactly where a previous run stopped (see Handling Edge Cases). - Unattended completion is the user's opt-in via the built-in
/goalcommand (see Step 0). The orchestrator's terminal outputs are the goal's verifiable end states:ALL_TASKS_COMPLETEon success,TASKS_BLOCKED: [...]when no progress is possible. Both are terminal — a blocked run ends the goal too, rather than leaving it spinning.
Output Summary
Final output should be one of:
Success:
ALL_TASKS_COMPLETE
Plan: {plan-name}
Total tasks: {N}
All tests passing.
Post-implementation hooks complete.
Commits created: {N}
## What Changed
{Brief, high-level summary of what was built or changed. Write this as a bulleted list
describing the user-visible outcomes — not implementation details. Derive this from the
completed task titles and the plan objective. For example:}
- Added visitor name column to the detail table
- Linked visitor rows to their detail pages
- Reordered columns to match design spec
- Added sorting to all new columns
NOTE: The "What Changed" section should read like release notes — focus on outcomes, not internals. Pull from the plan's objective and completed task summaries.
After displaying the success output, prompt the user about pushing and creating a PR:
Would you like to push this branch and create a pull request?
1. **Yes, push and create PR** - I'll push feature/{plan-name} and open a PR
2. **Just push** - I'll push the branch, you can create the PR later
3. **No thanks** - Keep everything local for now
Never push or create a PR without the user's explicit permission. Wait for their response before taking action. If they choose option 1, push and use gh pr create with a summary derived from the plan objective and "What Changed" section.
Linking GitHub Issues: Check _plan.md for the ## Related Issues field. If it contains issue references (e.g., Closes #18), include them in the PR body so GitHub automatically links and closes the issues when the PR is merged. Place them at the end of the PR body, each on its own line.
Blocked:
TASKS_BLOCKED: [003, 007]
Plan: {plan-name}
Completed: {X}/{N}
Blocked tasks:
003: {blocked reason}
007: {blocked reason}
Manual intervention required for blocked tasks.
Partial Progress (for visibility during execution):
Batch {X} complete.
Progress: {completed}/{total}
Continuing...
Performance Expectations
With proper parallelization:
- 10 independent tasks: ~1-2 batches
- 50 tasks with shallow dependencies: ~3-5 batches
- 100 tasks: ~5-10 batches
Each batch runs tasks in parallel, dramatically reducing total time compared to sequential execution.