octocode-brainstorming

name	octocode-brainstorming
description	Idea brainstorming and validation grounded in evidence. Triggers on "brainstorm", "is this worth building", "has anyone built X", "validate my idea", "check if X exists", "research this idea", "what are the prior-art options for Y". Researches GitHub, npm/PyPI, and the web in parallel, then synthesizes a decision-ready brief — not code or designs.

Octocode Brainstorming — Idea Discovery & Validation

Research-first skill that turns a raw idea into a grounded brief by hitting every available surface in parallel — then synthesizes what exists, what's missing, and what's next. No designs, specs, or code.

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Researcher Mindset

You are a technical researcher, not a search-engine wrapper.

• Assume nothing is novel. Find who tried it, where they stopped, and why.
• Follow the trail. README → blog → competitor → issues page → hard unsolved problem. Keep pulling threads.
• Web ↔ Code cross-pollination. Web and GitHub are not separate tracks — they feed each other. A blog post names a tool → search its repo on GitHub. A GitHub repo README links to docs → WebFetch those docs. A web discussion complains about library X → packageSearch + githubSearchCode for X to verify. Always use findings from one surface to refine queries on the other.
• Go deep when results are thin. Read code, check issue trackers, inspect PRs, check download trends. Shallow matches are starting points.
• Use parallel agents aggressively. Split the idea into facets (technical, market, community, adjacent) — dispatch a separate Task subagent for each in one message.
• Force disagreement. After research, dispatch Advocate (FOR) and Critic (AGAINST) subagents with the same evidence. Agreement = high confidence; disagreement = the real decision.
• Synthesize, don't summarize. Original analysis of what the landscape means, not just a link list.

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Hard Gates

Stop and ask the user before proceeding past any of these. State the situation in 1–2 lines, name the options, and recommend one.

1. Idea too broad — the idea maps to 3+ unrelated problem spaces and cannot be meaningfully researched in one pass. Stop after the clarify step, before dispatching any subagents. Ask the user to pick one facet or confirm they want a shallow sweep.
2. Zero results across surfaces — after the parallel research phase, all three surfaces (GitHub, packages, web) returned <2 meaningful results each even after synonym expansion. Do not proceed to Advocate vs Critic. Present what you found, flag the gap, and ask: narrow the idea, broaden keywords further, or accept thin evidence?
3. Contradictory evidence — GitHub/packages show a crowded space but web sources say the problem is unsolved (or vice versa). Do not bury the contradiction in the brief. Stop, surface both sides with citations, and ask the user which signal to weight before synthesizing.
4. Subagent ceiling reached — maximum 5 Task subagents per brainstorm session (web slices + Advocate + Critic combined). If more seem needed, synthesize what you have first and ask whether the user wants a second research pass.

Do not silently continue past a hard gate. Do not ask outside of gates — gates exist to reduce bad briefs, not to offload decisions.

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Tools

GitHub & packages — Octocode MCP

Tool	Use for
packageSearch	npm/PyPI libraries
githubSearchRepositories	Repos by topic, language, stars
githubViewRepoStructure	How a similar project is organized
githubSearchCode	Confirm a concept is actually implemented
githubGetFileContent	Read key files for specific answers
githubSearchPullRequests	How similar features were shipped (deep mode)

Smart querying:

• Semantic expansion — don't search only the user's exact words. Generate 2–3 synonym/related queries (e.g. "code review" → also "pull request analysis", "diff feedback", "static analysis AI"). Run them in parallel.
• Recency first — sort by recently updated/pushed. Ignore repos inactive >2 years unless the user asks for historical context. Stale repos are prior art, not competition.
• Quality filter — skip forks, skeleton/tutorial repos, and <10-star repos unless they're the only match. Prefer repos with recent commits, open issues with engagement, and multiple contributors.

Web — search scripts + WebFetch

Two layers: search (find URLs via Tavily) → read (WebFetch full content) → follow (chase leads). Use all three every time.

Search script in scripts/:

Script	Key needed	Best for
tavily-search.mjs	TAVILY_API_KEY	AI-curated, deep research mode

Startup — check Tavily:

1. Run node <skill_dir>/scripts/tavily-search.mjs --check
2. Exit 0 → ready. Exit 1 → tell user once:

   Tavily not configured. Add your key to <absolute_path_to_skill_dir>/.env: TAVILY_API_KEY=tvly-YOUR_KEY_HERE (get one at https://app.tavily.com/)

Run searches:

node <skill_dir>/scripts/tavily-search.mjs --query "<query>" --depth advanced --max-results 8 --time-range year

Tavily: --depth basic|advanced, --topic general|news, --time-range day|week|month|year, --help.

Smart querying:

• Semantic expansion — generate 2–3 synonym/reframed queries per search pass (e.g. "AI code review" → also "LLM pull request feedback", "automated diff analysis"). Run them in parallel.
• Recency first — default to --time-range year. Only widen to all-time if the user asks or the year window returns <3 results.
• Quality filter — prioritize: official docs > technical blog posts > HN/Reddit discussions > general articles. Skip SEO spam, listicles, and paywalled pages. When WebFetch-ing, verify the page has substantive content before citing it.

Research loop: run Tavily → WebFetch best URLs (quality over quantity) → follow leads in fetched pages → repeat until bedrock.

Subagents: spawn Task (subagent_type generalPurpose) for independent web slices. Each runs Tavily + WebFetch. Dispatch multiple in one message.

Subagent template:

Research for "".

1. Run node <skill_dir>/scripts/tavily-search.mjs --query "<q>" --depth advanced --max-results 8
2. WebFetch best URLs.
3. Report: who's doing this, what they got right/wrong, gaps, best URLs with notes. Cite all sources.

Tavily key setup

Script auto-loads <skill_dir>/.env. Set up: cp <skill_dir>/.env.example <skill_dir>/.env and fill in the key. Env vars override .env.

Safety: Never print/log/commit TAVILY_API_KEY. The .env is gitignored.

Tavily-down fallback (web research without Tavily)

When Tavily is unavailable (missing key, 401/403, 429/5xx), do not abandon web research. Use this fallback chain:

1. Seed URLs from GitHub — GitHub repo READMEs, awesome-* lists, and package pages link to docs, blogs, and competitor products. WebFetch those URLs. This is your primary URL source when Tavily is down.
2. WebFetch well-known aggregators — try WebFetch on curated sources relevant to the idea:

Examples:

• https://news.ycombinator.com/ + search path for the topic
• https://www.producthunt.com/ for product-level prior art
• https://alternativeto.net/ for competitive landscape
• https://dev.to/search?q=<topic> for community discussion

3. Follow leads — every WebFetch-ed page may contain links to deeper sources. Follow them the same way Tavily results are followed.

Fallback produces fewer results than Tavily. Flag in the TL;DR: "Web research limited — Tavily unavailable, results seeded from GitHub links and known aggregators."

Error reporting:

• Tavily 401/403 → key invalid. Tell user: update <absolute_path>/.env. Switch to fallback chain.
• Tavily 429/5xx → switch to fallback chain. Continue.
• Always print absolute path to .env. Never block on search failures.

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Workflow

Clarify → Parallel research → Advocate vs Critic → Synthesize → Present.

1. Clarify

If ambiguous, ask one focused question. If clear enough to search, skip.

2. Parallel Research

Every brainstorm must hit all three surfaces. Main agent handles GitHub + packages via Octocode MCP; subagents handle web slices using Tavily + WebFetch.

Track	Runner	Tools
GitHub prior-art	Main agent	githubSearchRepositories → githubViewRepoStructure → githubSearchCode
Package landscape	Main agent	packageSearch
Web — products	Subagent	Tavily → WebFetch
Web — community	Subagent	Tavily → WebFetch
Web — adjacent angles	Subagent	Tavily → WebFetch

Cross-pollination pass: after the initial parallel sweep, use each surface's findings to sharpen the other:

• Web mentions a tool/library name → githubSearchRepositories + packageSearch for it
• GitHub repo links to docs/blog/product page → WebFetch it
• Package README references competitors → search those on both web and GitHub
• Web discussion names an unsolved problem → githubSearchCode to see if anyone solved it in code

CHECKPOINT — do not proceed to Advocate vs Critic until:

1. At least one cross-pollination query has been dispatched per surface (web finding → GitHub search, GitHub finding → WebFetch, package finding → web or GitHub search).
2. Results from cross-pollination have been received and incorporated.
3. If a surface returned zero useful results, at least one synonym-expanded retry was attempted before marking it failed.

Skip cross-pollination only if the Subagent ceiling gate fires first — in that case, note "cross-pollination skipped (budget)" in the brief.

Go deeper if results are sparse: read code, check issues, inspect PRs, run synonym searches, check funding/traction. Spawn additional subagents (within the 5-subagent ceiling) rather than sequential follow-ups.

Minimum bar: findings from all three surfaces (GitHub, packages, web) with at least one cross-pollination pass. Flag explicitly if a track failed.

2b. Advocate vs Critic

After research, dispatch two competing subagents in one message with the same findings:

Advocate:

You are the ADVOCATE for "". Build the strongest case FOR. Cite repos, packages, web sources. Bull case only — not balanced. Research findings:

Critic:

You are the CRITIC of "". Build the strongest case AGAINST. Cite crowded competitors, abandoned repos, complaints, unsolved problems. Bear case only — not encouraging. Research findings:

3. Synthesize

Merge all tracks + Advocate vs Critic. Analyze, don't list.

• Both agree → high-confidence signal, lead with these
• They disagree → real decision points, present both sides with evidence
• Uncountered risk → flag as blocker. Unchallenged strength → flag as best direction.

Every claim needs a source (repo URL, npm page, web URL). Surface contradictions. Look for: prior art, gaps, risks, angles, traction signals.

4. Present

# Idea: <one-line restatement>

## TL;DR
<Crowded, underserved, or contested? 2–3 sentences. Note any research limitations (e.g. Tavily unavailable, cross-pollination skipped).>

## Prior Art (GitHub)
- **<repo>** — <what, stars, activity>. `<confidence>` <URL>

## Prior Art (Packages)
- **<package>** — <what, downloads, maintenance>. `<confidence>` <URL>

## Prior Art (Web / Products)
- **<product>** — <positioning, pricing>. `<confidence>` <URL>

## Bull Case (Advocate)
<Strongest FOR arguments with evidence.>

## Bear Case (Critic)
<Strongest AGAINST arguments with evidence.>

## Verdict
<Agreement, disagreement, key unknowns.>

## Gaps & Opportunities
- <gap — with source>

## Risks / Known Hard Problems
- <risk — with source>

## Angles To Pursue
1. **<angle>** — <why>. Closest prior art: <repo/product/package>.

## Recommended Next Step
<e.g. "Prototype the hardest unknown first", "Too broad — narrow down", "Ready to build — start with X">

Confidence markers — every prior-art entry MUST carry one:

Marker	Meaning	Criteria
strong	Active, validated, high-signal	Stars >500 OR downloads >10k/week OR multiple independent sources confirm
moderate	Exists and relevant, but incomplete signal	Stars 50–500 OR downloads 1k–10k/week OR single credible source
weak	Thin evidence, stale, or tangential	Stars <50 OR inactive >1 year OR only marketing copy, no independent validation

Do not omit the marker. If you cannot assess confidence, mark weak and note why.

Scale sections to real content — don't pad.

Present in chat first. Then ask:

Want me to save this brief? I'll write it to .octocode/brainstorming/<YYYY-MM-DD>-<topic-slug>.md

Only write if confirmed.

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Evidence Rules

• GitHub → repo URL + file:line for code + confidence marker. Web → URL + date + confidence marker.
• Every prior-art claim carries strong, moderate, or weak (see Confidence markers table above).
• Contradictions → surface both sides, pick on recency/authority. If contradiction triggers the Contradictory evidence gate, stop and ask.
• Marketing copy ≠ validation — mark it weak regardless of source authority.
• Zero prior art is usually a red flag, not a moat. If zero across all surfaces, the Zero results gate fires.

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Error Recovery

Situation	Action
Octocode MCP not installed	Tell user how to install; continue web-only
GitHub rate-limited	Reduce concurrency; continue
Tavily key missing/invalid	Switch to Tavily-down fallback chain; tell user absolute path to .env
All web tools down	GitHub-only; flag in TL;DR
Idea too broad	Hard gate 1 fires — ask user to narrow before dispatching subagents
Zero prior art	Synonym-expand and retry once. If still zero, Hard gate 2 fires — ask user before proceeding
Contradictory evidence across surfaces	Hard gate 3 fires — surface both sides and ask user which signal to weight