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◗ Agentic workflow · reference card

Superpowers + Compound V

The two-plugin toolchain for shipping real work with an AI squad: brainstorm a spec, audit the ground, plan a disjoint partition, then route every task to the right model and backend in parallel behind hard review gates, and it remembers what it learns.

Superpowers, the skeleton: brainstorm → plan → TDD → review
Compound V, expert planning, parallel multi-model dispatch & accumulating memory

A The golden path

idea → merged

One-time per project: /v:init, detect backends, pick a routing stance, save config. Then, per feature:

1

Brainstorm the spec superpowers

Say brainstorm <idea> (or "let's build X"). One-question dialogue + 2-3 approaches → an approved spec in docs/superpowers/specs/. Hard gate: no code before the design is approved.

2

Pre-flight audits the real "onboard"

Three agents in parallel case the territory, code-archaeologist (what exists), domain-expert (the rules), doc-validator (library/API reality). /v:archaeology runs just the code audit.

3

Plan a partition superpowers

Spec → a bite-sized plan with a verified Partition Map: disjoint write-paths per task, so agents never collide.

4

Cross-model plan review by stakes

/v:review-plan, a different model family (Codex) adversarially reviews the plan read-only; you arbitrate. Run it for security / auth / payments / migrations, big partitions, or architectural change.

5

Materialize the manifest

/v:orchestrate writes manifest.yaml + state.json. It does not dispatch, inspect or edit first.

6

Dispatch in parallel

/v:dispatch, batched multi-backend execution. partition-reviewer + validate-manifest gate first; the git-diff scope gate runs after every job. A bare plan path auto-materializes.

7

Recover & inspect

/v:resume reconciles state against git (git wins) and re-runs only incomplete jobs. /v:status shows the phase, a per-job table, and backend health.

8

Review gate → rework → merge

Three passes, SPECQUALITYINTEGRATION, checked by a different family. Any issue bounces the job back to the bench for a fix, then re-review. Only all-green merges. No "close enough".

Phases: SPEC_READY → PREFLIGHT_DONE → PARTITION_VERIFIED → DISPATCHED → COLLECTED → REVIEWED → MERGED  ·  /v:epic chains several features into one autonomous, resumable, dependency-ordered build, each runs the full path above.

B Compound V commands

/v:*

/v:init
One-time setup: detect backends (Codex, Context7, Antigravity), pick a routing stance, save .claude/compound-v.json.
/v:archaeology
Run just the Phase-1A code archaeology audit.
/v:review-plan
Cross-model (Codex) adversarial plan review; you arbitrate.
/v:orchestrate
Materialize the manifest. Never dispatches.
/v:dispatch
Execute via batched parallel multi-backend dispatch.
/v:collect
Re-run the collect + scope-gate + review tail of a run.
/v:resume
Recover an interrupted run; re-dispatch only what's incomplete. Idempotent.
/v:status
Read-only: phase + per-job table + backend health.
/v:epic
Chain features into one autonomous, resumable build.
/v:models
Refresh the tier → model map. Run when a provider ships a new model.
/v:remember
Recall past context via V-memory (semantic). Evidence, not a ruling.
/v:memory-refresh
Reindex docs/superpowers into the local V-memory cache.

C Superpowers skills

not commands · auto-fire

SkillTrigger & purpose
brainstorming"let's build X" → dialogue → approved spec. No code before approval.
writing-plansspec → task-by-task plan (paths, code, TDD, commits).
subagent-driven-developmentrecommended fresh subagent per task + two-stage review.
executing-planssequential execution with checkpoints (separate session).
test-driven-developmentRED → GREEN → REFACTOR. No prod code without a failing test.
verification-before-completionrun the real command now before claiming done.
systematic-debuggingroot cause before any fix; 3+ failed fixes = architecture problem.
requesting / receiving-code-reviewreviewer subagent on a real diff; verify feedback before applying.
using-git-worktreesisolated workspace; detect existing isolation first.
finishing-a-development-branchmerge / PR / keep / discard, then clean up.

D V-memory

semantic project recall

A local-first recall layer over docs/superpowers/** prose, specs, plans, reviews, audits, lessons. It answers "have we seen this before?" by meaning, not filename grep, and accumulates as the project grows: every plan and postmortem you commit becomes searchable on the next refresh. It stays subordinate, evidence for planning & review, never a routing input.

Two lanes

FTS5, BM25, always on, pure stdlib, offline, instant. The dependable substrate.

Embeddings, multilingual-e5-small, opt-in, cached outside the repo. Kicks in for large corpora; absent → silently FTS5-only.

recall-check: a file pattern with ≥2 prior blocked/error jobs → verdict tighten (force worktree / +1 review / fold into Task 0). Conservative-only, it can only tighten.

v-memory
# recall past context as evidence
/v:remember "notion oauth token refresh"

# reindex (+ optional semantic lane)
/v:memory-refresh --with-embeddings

# the engine, directly
python3 scripts/compound-v-memory.py bootstrap   # the ONLY network step
python3 scripts/compound-v-memory.py refresh --with-embeddings
python3 scripts/compound-v-memory.py search "<q>" --intent planning
python3 scripts/compound-v-memory.py doctor      # index / venv / health

E Backends & routing

who does what

V routes by tier, not a hardcoded model, the concrete model resolves at dispatch from a refreshable map (/v:models), so it survives model churn. haiku is never used.

light
effort · low

mechanical single-file edits, docs, i18n, well-specified CRUD.

standard
effort · medium

bounded feature build, including large-isolated Codex work.

deep
effort · high

architecture, sensitive surfaces, new tests, external APIs, every reviewer, Task 0.

BackendTrustRole
claudekernel-trusted, in-processdefault; Task 0, sensitive surfaces, reviewers, docs
codexkernel-sandboxed worktreerecommended ally for large-isolated build
antigravitylower-trust worktreeopt-in extra hands, trusted surface only
cursorlower-trust worktreesame tier & caveats as antigravity
Hard invariants · enforced deterministically
  • reviewers ⇒ deep (opus)
  • codex / antigravity / cursor ⇒ worktree
  • run: parallel ⇒ isolation: worktree
  • unclear scope ⇒ back to planning
  • scope gate: any write outside write_allowed ⇒ blocked, never merged

Stances (pick at /v:init): Balanced (default, with Codex) · Claude-only (Codex absent → rows collapse to claude/deep) · Conservative · Cost-aware, but sensitive surfaces & reviewers stay deep in every stance.

F Optimal setup

subscriptions

$200
Claude Max
the trust-critical seat

Funds the deep / reviewer / Task-0 work, architecture, every sensitive surface, all reviewers. This is what's never cost-optimized in any stance, so it needs the highest-trust, in-process backend.

$100
Codex
throughput + 2nd family

Runs as its own sandboxed process/worktree, so large builds parallelize off Claude's plate, and a different model family gives you the error-decorrelation the review layer is built on. Cheaper than a second Opus seat.

+ Antigravity
optional
extra cheap hands

Extra parallel capacity, worth adding only once you have trusted, narrow-blast-radius build work, no kernel write-confinement, so the gate detects leaks but can't prevent out-of-worktree side effects.

The plugin forbids fabricated cost/token numbers ("anti-ruflo"), so this stays at the subscription-tier level, the $200 seat funds work that can't be cheapened; the $100 seat funds parallel throughput plus a second opinion.

G Skills for the Universal Creator

founder brain

Compound V is the build engine. These skill packs add the solo founder's brain, product, marketing, thinking and anti-slop copy, so one person can own the whole product.

Marketing Skills →

60+ marketing skills: CRO, copy, SEO, ads, launches, pricing. The whole go-to-market a solo builder owns.

/plugin marketplace add coreyhaines31/marketingskills

Product Manager Skills →

55 PM skills: discovery, RICE/ICE/Kano prioritization, PRDs, roadmaps. Structure for what to build.

/plugin marketplace add deanpeters/Product-Manager-Skills

Thinking Skills →

39 mental models: first principles, inversion, pre-mortem, JTBD, red-team. To pressure-test the concept.

/plugin marketplace add tjboudreaux/cc-thinking-skills

Stop Slop →

Detects and strips AI writing patterns and scores directness. Keeps your PRD and launch copy human.

git clone https://github.com/hardikpandya/stop-slop.git
The whole thing in one line

Brainstorm the spec → audit the ground → plan a disjoint partition → let V route each task to the right model + backend in parallel → gate everything (scope + 3-pass cross-model review) → rework what fails → merge. V-memory quietly remembers all of it, so the next run starts smarter.

Superpowers 6.1.1 · Compound V (superpowers-v) 2.1.1 procoders/superpowers-v · obra/superpowers