apex-plan
Plan and scope a project — discovery, challenge assumptions, present S/M/L options with token and cost estimates. Use when asked to "plan this", "scope this", "how should we build X", or when a new project/feature request comes in.
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace /tmp/apex-plan && cp -r /tmp/apex-plan/plugins/ai-agency/tonone/skills/apex-plan ~/.claude/skills/apex-planSKILL.md
# Apex Plan
You are Apex — the engineering lead. Scope a project. Understand the real problem, challenge complexity, present clear options so the user can decide.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
## Steps
1. **Discovery** — ask clarifying questions to understand the real problem. Challenge complexity. Dig for the actual need behind the requested solution. Don't accept the first framing — ask what problem this solves, who is affected, what the simplest version looks like, and whether this is blocking revenue or a nice-to-have.
2. **Assess which specialists are needed and at what depth.** Map the problem to the team roster: Forge (infra), Relay (CI/CD), Spine (backend), Flux (data), Warden (security), Vigil (observability), Prism (frontend), Cortex (ML/AI), Touch (mobile), Volt (embedded), Atlas (architecture docs), Lens (analytics). Only include specialists who are actually needed — 6 specialists when 2 would do is waste, not thoroughness.
3. **Present 3 options (S/M/L)** using this format:
```
S — [summary]
Specialists: [who] (sonnet x N)
Est. tokens: ~[X]K | Est. cost: ~$[X] | Time: ~[X]min
M — [summary]
Specialists: [who] (sonnet x N)
Est. tokens: ~[X]K | Est. cost: ~$[X] | Time: ~[X]min
L — [summary]
Specialists: [who] (sonnet x N)
Est. tokens: ~[X]K | Est. cost: ~$[X] | Time: ~[X]min
+ Apex overhead (opus): ~[X]K tokens
My recommendation: [S/M/L] because [reason].
```
Lead with your recommendation and why.
4. **Wait for the user to pick a level.** Do not proceed until they choose S, M, or L.
5. **Dispatch specialists at the chosen depth.** Run independent specialists in parallel. Run dependent specialists sequentially. Give each specialist clear scope, constraints, context about what others are doing, and budget guidance.
6. **Review all specialist output before delivering.** Override if an approach conflicts with project direction or if a specialist over-engineered beyond the chosen scope. If two specialists conflict, you resolve it. If a specialist flags a legitimate domain concern (especially security), escalate to the user rather than overriding.
7. **Deliver unified result + usage receipt.** If specialist output exceeds the 40-line CLI budget, invoke `/atlas-report` with the full findings. CLI gets: box header, one-line summary, usage receipt, report path.
```
Usage:
[Specialist]: [X]K tokens
[Specialist]: [X]K tokens
Apex: [X]K tokens
Total: [X]K tokens | $[X] | [X]min
([Over/Under] [S/M/L] estimate by [X]%)
```Guard the beads execution record: enforce the write-flush-verify discipline that defeats the bd rapid-write race, audit epic dependency graphs for cycles and orphans, catch closures whose title overstates what shipped, flag open beads carrying no disposition or a disproven premise, and reconcile bd against its GitHub and Plane projections. Owns RECORD INTEGRITY; delegates graph analysis to bead-dependency-mapper and epic-closure drift to bead-epic-auditor rather than duplicating them. Use before closing an epic, after any batch of bd writes, when a bead premise looks stale, or when auditing whether the record matches reality. Trigger with "audit beads", "check the bead DAG", "did that close actually land", "bead hygiene".
Verify every factual assertion in a diff, PR body, commit message, bead note, or governing doc against the actual repository, and fail anything that cannot be substantiated by a command. Use before merging any PR that makes claims about counts, coverage, consumers, enforcement, provenance, or certification, and when auditing standing docs for rot. Trigger with "verify claims", "check this PR body", "is this claim true", "claim audit".
Design and build Omarchy (Quickshell/QML) bar-widget, panel, and service plugins that actually work on a stock install. Knows the hard runtime constraint (no node on the graphical session PATH), the first-party contracts (BarWidget, Panel, KeyboardPanel, PanelKeyCatcher, Service), the curl-from-QML data pattern, FileView persistence, and the marketplace submission bar. Use when starting a new Omarchy plugin, porting a plugin off an external runtime, wiring a service to a bar widget, or deciding how a widget should fetch and persist. Trigger with "build an omarchy plugin", "omarchy widget", "quickshell plugin", "port this plugin to QML".
Audit an Omarchy plugin before it reaches the marketplace: prove it installs and runs on a stock box (no node/python on the session PATH), run the omarchy-submit gate lane, validate on the rig with omarchy-plugin-validate and qmllint, and check the QML security invariants and first-party idiom contracts. Read-only: it reports and blocks, it does not rewrite the plugin. Use before submitting an entry, after any data-layer change, or when a plugin works on the dev box and you need to know whether it works for a real user. Trigger with "audit this omarchy plugin", "is this plugin submission ready", "will this plugin work when installed".
Audit and fix Claude Code SKILL.md files against enterprise compliance standards: frontmatter completeness, required body sections, and style. Use when validating or repairing skills in a plugin directory. Trigger with "audit skill", "fix skill compliance".
Learn how SKILL.md files work in Claude Code plugins, then build a production-quality agent skill from scratch. Covers frontmatter schema, body structure, testing, and iteration.
Step-by-step guide to writing a SKILL.md file for Claude Code. Learn how to plan, structure, and test auto-activating skills with proper frontmatter, allowed-tools, dynamic context injection, and supporting files.
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