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Pure-Water-Automations/agent-skills

Use when the user wants a multi-perspective brainstorm on a feature, app, or product area — "spin up agents with different personalities/job titles", "look at it from different angles", "panel of experts", "come up with 30 ideas and a top 5", "how can we make X more useful", "brainstorm what to do next with X" — especially when they also want to DECIDE on the ideas (implement / hold / reject) rather than just read a list. Also use when they ask to re-run or extend a previous panel, or to "make the ideas decidable like dev-to-prod-promotion-review".

What is agent-skills?

agent-skills is a Claude Code agent skill that use when the user wants a multi-perspective brainstorm on a feature, app, or product area — "spin up agents with different personalities/job titles", "look at it from different angles", "panel of experts", "come up with 30 ideas and a top 5", "how can we make X more useful", "brainstorm what to do next with X" — especially when they also want to DECIDE on the ideas (implement / hold / reject) rather than just read a list. Also use when they ask to re-run or extend a previous panel, or to "make the ideas decidable like dev-to-prod-promotion-review".

Works with✓Claude Code✓Codex CLI~Cursor✓Antigravity
npx skills add https://github.com/Pure-Water-Automations/agent-skills/tree/HEAD/panel-brainstorm

Ask in your favorite AI

Open a new chat with this agent skill pre-loaded.

Documentation

Panel Brainstorm → Interactive Decision Board

If a LOCAL.md file sits next to this SKILL.md, read it first — it holds this workspace's specifics (paths, tools, examples) and overrides the generic defaults below.

Run a persona panel across Codex / Antigravity / Claude credit pools to generate grounded product ideas, stress-test them with an adversarial CPO pass, synthesize a deduped ~30-idea list with a wireframed top 5, and publish an interactive decision board (Implement / Hold / Reject per idea) whose copied summary comes back into chat as the decision of record.

Reference output (a real panel, anonymized): assets/decision-board-reference.html.

When NOT to use

  • A single well-scoped feature request → just build/plan it (or superpowers:brainstorming inline).
  • Code review or promotion decisions on an existing branch → dev-to-prod-promotion-review.
  • Pure research questions → deep-research.

Procedure

1. Ground yourself first (main thread)

Read the actual code/feature being brainstormed about. Write a 3–6 line current-state summary (what it does today, key files, known limits). Every persona prompt embeds this summary plus the concrete file paths to read — this is what keeps ideas grounded instead of generic.

2. Design the panel

5–7 personas, each with a name, job title, and a lens that produces different ideas — not different wordings of the same lens. The proven mix:

Persona archetypeLensGood backend
Staff engineer ("Dex")cheap & high-leverage given existing codecodex
Growth PM ("Priya")activation, habit loops, measurementcodex
UX designer ("Wren")lost users, wayfinding, accessibilityantigravity (≤1 leg)
Power-user operator ("Marisol")the busy operator's actual dayclaude
Nervous newcomer ("Jomar")day-3 confusion, reassurance, languageclaude
AI strategist ("Kade")agentic frontier, mapped onto existing machinery, risksclaude

Swap archetypes to fit the subject (e.g. a client persona, a bookkeeper). Keep at least one user persona (not a builder) and one skeptic-adjacent lens.

Each persona task: "BRAINSTORM TASK (write a markdown doc, do NOT change app code)… propose exactly 8 ideas… for each: short name, one-line pitch, why/moment it serves, how it would work (grounded in the files you read), effort S/M/L. Write to docs/<topic>-ideas/<persona>.md. That file is your ONLY deliverable."

3. Run it as a parallel fan-out

Use whatever parallel runner you have: a multi-backend fan-out tool that runs each persona as an independent background job in its own git worktree (Codex / Antigravity / Claude), or native background subagents (max 3 concurrent, waves if more). Additions specific to panels:

  • An adversarial review pass (a final job that reads every persona doc) with a product-panel focus, not a code review: "You are a skeptical Chief Product Officer chairing a product panel… critique each panelist's ideas for realism and impact, call out overlaps, end with your ranked top 8." The CPO verdicts become per-idea annotations later.
  • Run in background; monitor for completion.

4. Verify deliverables — backends can lie

After the run, check every persona's output file actually exists (ls the worktrees). Antigravity can report status: done having written nothing. Re-run any missing persona as a native background subagent (same prompt, "return the ideas as your final message, do not write files") — takes ~1 minute.

Also: the review's final ranked list can be truncated in the runner's report files. The per-idea critiques usually survive; do the final ranking yourself.

5. Synthesize

  • Dedupe ~48 raw → ~30 ideas grouped into 5–6 themes; keep persona attribution (convergence = multiple personas proposing the same thing is the strongest ranking signal).
  • Pick a top 5 by: convergence → CPO verdict → fit with existing code.
  • Note what the panel cut and why (one line) — the user wants to see the kills.
  • Persona docs live in the runner's worktrees that get cleaned up; if worth keeping, copy them out before running any cleanup.

6. Build the interactive decision board (Artifact)

Adapt assets/decision-board-reference.html — keep its CSS kit and the entire <script> verbatim except STORE_KEY (must be unique per board or two boards clobber each other's decisions). Load the artifact-design skill before writing.

Required elements (the dev-to-prod-promotion-review pattern):

  • Sticky live tally — implement / hold / reject / undecided counts.
  • Top-5 cards with a CSS-only wireframe of the change (the reference has a reusable wireframe kit: .wf, .frame, .side, .bub, .rankrow, .spot, .note) + persona attribution + a CPO check: callout.
  • 3-way toggle (✓ Implement / ◦ Hold / ✕ Reject) on every top-5 card AND every row of the 30-idea table. Decisions live at leaf-idea granularity: a bundle card sets data-key plus data-also="iX,iY" so deciding the card decides its constituent ideas, and the table rows stay individually adjustable. Clicking the active choice again clears it.
  • localStorage persistence keyed by the unique STORE_KEY.
  • Decision summary textarea + Copy button — Artifacts have no sendPrompt bridge; the copied text pasted back into chat IS the return channel. Include a Reset button.

Verify before publishing: serve the file over a local python3 -m http.server (the browser pane's file:// preview is flaky) and click-test with javascript_tool: bundle click sets constituents, tally updates, localStorage persists, reset clears. Mojibake in the local preview is just the missing charset header — the published Artifact sets one.

Publish with the Artifact tool; republish the same file path to keep the URL.

7. Report and collect decisions

Final chat message: top 5 in one line each + artifact link + note that decisions copy back into chat. When the user pastes the summary back, treat it as the decision of record: honestly reconcile it against your own ranking (a surprise reject is signal, not noise), then plan/execute the IMPLEMENT list and park HOLD items where they say.

Common mistakes

MistakeFix
Personas without file paths to readGeneric ideas — always embed current-state summary + paths
Trusting agy's done statusCheck the output file exists; re-run leg as native subagent
Decisions at bundle granularity onlyLeaf ideas decide; bundles fan out via data-also
Reusing a STORE_KEYTwo boards overwrite each other's localStorage decisions
Cleaning worktrees before copying persona docsDocs are on worktree branches — copy out first if keeping
Skipping the CPO passUnranked wish-list; the critiques are half the value
Waiting for the CPO's ranked listIt truncates; rank yourself from convergence + verdicts

Individual skills in this repo

This repo contains 2 individual skills — each has its own dedicated page.

Pure-Water-Automations/agent-skills

Score any app (the user's own or a competitor's) on a research-backed rubric and produce a reusable, comparable scorecard — 0–5 per dimension with an evidence grade, noncompensatory gates checked first, and one "smallest fix" per weak dimension. Adapts to product stage: a pre-PMF app under ~100 users is scored on 9 dimensions, a growth-stage app on the full 23. Use whenever the user says "score this app", "grade the app", "rate the UI/UX", "how good is [app]", "app scorecard", "run the scorecard on [app]", "how does [app] stack up", "is this ready to launch / promote to prod", or wants a before/after number after a build sprint or a beta round. Reads the codebase + deploy + docs, optionally beta feedback / analytics, and refuses to invent retention, revenue, or PMF from code alone. Outputs a chat table plus a published HTML scorecard artifact. Pairs with ui-usability-audit (UI depth), qa-sweep (functional pass), dev-to-prod-promotion-review (release gate).

Pure-Water-Automations/agent-skills

>- Use when the user wants to improve or rethink a feature of one of their apps by learning from competitor products — "look at how Loom/Notion/Linear does it", "spin off agents to screenshot ours and competitors", "what can we learn from other apps for X", "benchmark our X against Y", "how can we improve the organization of X" — especially when they also want to SEE the proposal (a before/after design of the improvements, current UI beside the redesign with the new pieces highlighted) before anything gets built.

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