Kreator · JetBrains
Pembaruan terakhir · 24 Agu 2026
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip th
Hanya sandbox
Target pemasangan
Prompt pemasangan Codex
Install the "brainstorming" agent skill from https://github.com/JetBrains/thinkrail/tree/main/packages/pi-thinkrail-workflow/skills/brainstorming. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jetbrains-brainstorming","task":"Install brainstorming","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Profil aset
Riset dan pekerjaan pengetahuan
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Skenario
Agent riset
I need my agent to research a topic, compare sources, and produce a concise report.
Kecocokan Agent
Claude Code + CLI + Codex
Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.
Pasang
Siap
npx skills add JetBrains/thinkrail --skill brainstorming
Pemeliharaan
Terkini
Diperbarui hari ini
Risiko
Perlu ditinjau
Financial research output is not financial advice; require human review before any live investment decision
Kualitas GitHub
38
62/100 Kualitas · 77/100 Kepercayaan
Tag cakupan
Catatan ulasan
Financial research output is not financial advice; require human review before any live investment decision · Low GitHub adoption signal
Kartu adopsi Agent
Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat
Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.
Kualitas
MenjanjikanUseful candidate, but compare it with alternatives before adopting.
Kepercayaan
Hanya sandboxKandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.
Audit
Perlu ditinjauTinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Trust Score OpenAgentSkill v5
Tinjauan manusia sebelum pemasangan
Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.
Star
38 star GitHub
Aktivitas repositori
38 star dan 8 fork
Pemeliharaan
Diperbarui hari ini
Lisensi
Apache-2.0
Pasang
npx skills add JetBrains/thinkrail --skill brainstorming
Keamanan pemasangan
Jalur pemasangan paket atau runtime standar
Cakupan izin
Akses sistem file atau dokumen
Hasil Agent
Belum ada data hasil Agent
Dokumentasi
Usable metadata, review docs
Ringkasan risiko
Tinjau sebelum produksi
- Financial research output is not financial advice; require human review before any live investment decision.
- Low GitHub adoption signal
- Quality score needs review
- GitHub adoption: 38 GitHub stars
Kesiapan pemasangan
Jalur pemasangan tersedia
- Jalur pemasangan tersedia
- Bukti repositori tersedia
- Lisensi dinyatakan
- Belum ada bukti hasil Agent-Proven
Metadata yang dapat dibaca Agent
Data keputusan yang dapat dibaca mesin untuk skill ini.
Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.
View technical data+
Metadata yang dapat dibaca Agent
Data keputusan yang dapat dibaca mesin untuk skill ini.
Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.
Tugas yang sesuai
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
- Sumber pencarian
Agent yang sesuai
Keputusan pemasangan
- Perintah
- npx skills add JetBrains/thinkrail --skill brainstorming
- Kebijakan
- Tinjau
- Tinjauan manusia
- Ya
Kepercayaan dan risiko
- Kepercayaan
- 69/100
- Audit
- 79/100
- Tingkat risiko
- Perlu ditinjau
Lingkar hasil
- Endpoint
- /api/agent/outcome
- ID event
- resolve
- Hasil
- 5
Perintah pemasangan
npx skills add JetBrains/thinkrail --skill brainstormingJangan gunakan ketika
- Tim yang membutuhkan SLA dengan dukungan vendor
- production agents without a repository review
- Low GitHub adoption signal
- No OpenAgentSkill engagement data yet
- Financial research output is not financial advice; require human review before any live investment decision
Skill alternatif
Last30days Skill
53.5K Star
npx skills add mvanhorn/last30days-skill -g
Skill alternatif
Academic Research Skills
38.4K Star
npx skills add Imbad0202/academic-research-skills
Skill alternatif
GPT Researcher
28.0K Star
npx skills add assafelovic/gpt-researcher
Skill alternatif
DeepResearch
19.8K Star
npx skills add Alibaba-NLP/DeepResearch
Keamanan Agent v2
63/100 · Tinjau sebelum memasang
Kandidat yang dapat digunakan, tetapi Agent harus menampilkan catatan izin dan audit sebelum memasang.
Memerlukan persetujuan manusia sebelum memasang ke workspace nyata.
Sedang
Akses jaringan
Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.
Sedang
Akses sistem file
Skill dapat membaca atau menulis file proyek, dokumen, artefak yang dihasilkan, atau status workspace lokal.
- Financial research output is not financial advice; require human review before any live investment decision
Rencana resolusi Agent
Biarkan Agent memverifikasi kecocokan sebelum memasang.
API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.
Buka JSON
/api/agent/resolve?task=Use%20brainstorming%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Teks Resolve
/api/agent/resolve?task=Use%20brainstorming%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Serah-terima pemasangan
/api/skills/jetbrains-brainstorming/install
Agent harus memeriksa
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Salin prompt
Task: Use brainstorming in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20brainstorming%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jetbrains-brainstorming/install
Install command: npx skills add JetBrains/thinkrail --skill brainstorming
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Serah-terima Agent
Berikan jalur pemasangan kepada Agent, bukan direktori lain.
Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.
Serah-terima pemasangan
/api/skills/jetbrains-brainstorming/install
Format teks LLM
/api/skills/jetbrains-brainstorming/install?format=text
Cari alternatif
/api/skills/search?q=brainstorming&limit=3
Prompt Agent
Use brainstorming for this task. Review https://www.openagentskill.com/api/skills/jetbrains-brainstorming/install, then install with: npx skills add JetBrains/thinkrail --skill brainstormingMetadata Registry
Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Manifest
/api/registry/manifest/jetbrains-brainstorming
Teks LLM
/api/registry/manifest/jetbrains-brainstorming?format=text
Alias pemasangan
/api/registry/install/jetbrains-brainstorming
Rekomendasikan
/api/registry/recommend?task=Use%20brainstorming%20in%20an%20agent%20workflow&limit=3
Kecocokan Agent
Agent riset
Tag use case
Platform
Claude Code
Laporan audit
Perlu ditinjau · 79/100
Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Panel keputusan Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Peran di stack
Kandidat cadangan
Kecocokan utama
Agent riset
Label kepercayaan
Buat prototipe dulu
Jalur pemasangan
Perintah siap
Gunakan saat
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
Bukti
- recent repository activity
- install command or GitHub repo available
- profil kualitas 62/100
tinjau dulu
- Low GitHub adoption signal
- No OpenAgentSkill engagement data yet
Jalur implementasi
- 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil kepercayaan
Hanya sandbox
Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.
Adopsi GitHub
Periksa38 star GitHub
Aktivitas star/fork
Periksa38 star dan 8 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
LulusDiperbarui hari ini
Kejelasan lisensi
LulusApache-2.0
Sinyal positif
- Tinjauan AI disetujui
- Jalur pemasangan tersedia
- Bukti repositori tersedia
- Repositori yang baru dipelihara
- Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
- Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama
Tinjau sebelum memasang
- Financial research output is not financial advice; require human review before any live investment decision.
- Low GitHub adoption signal
- Quality score needs review
- GitHub adoption: 38 GitHub stars
- Stars/forks activity: 38 stars, 8 forks; issue activity unavailable in current metadata
- Belum ada laporan hasil Agent nyata
- Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan
Tindakan yang disarankan
Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.
Profil kualitas
Menjanjikan kandidat untuk alur kerja Agent
Useful candidate, but compare it with alternatives before adopting.
Kecocokan alur kerja
Gunakan skill ini pada skenario berikut
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Kecocokan alur kerja
Tambahkan ke alur kerja lengkap
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Daftar alternatif
Bandingkan sebelum memasang
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Ringkasan
--- name: brainstorming description: "Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small." ---
# Brainstorming
## Brainstorm before you build
- Before starting any creative or feature work — a new feature, added functionality, a behavioral change, a nontrivial design decision — stop and run this workflow before writing implementation code. - The aim: turn the request into a validated design, recorded as a spec-graph `task-spec`, that the user has explicitly approved — not a guess you implement and hope lands. - Never implement during brainstorming. If you catch yourself opening a source file to make a change before the design is approved, stop.
## Anti-pattern: "this is too small to need this"
Every request goes through this, however small it looks. A one-line config change and a new subsystem both benefit from a few minutes of "what does the user actually want and why" — that is where wrong assumptions get caught cheaply. Scale the *depth* to the task; never skip the workflow entirely.
## The workflow
1. **Orient.** Use the spec-graph skill's tools first — `spec_grep`/`spec_get`/`spec_graph` — to find what the project already says about the area; read code second, to confirm details. 2. **Scope check.** If the request bundles multiple independent features or subsystems, say so and brainstorm them one at a time (or in parallel sub-sessions, the user's call) — don't blend unrelated decisions into one task-spec. 3. **Open a task-spec.** As soon as you understand roughly what's being asked, `spec_create` a `task-spec` at **`.thinkrail/context/TASK-<slug>.md`** (id, title, status: draft, parent: the nearest relevant module) to hold the design as it develops. `.thinkrail/context/` is the workspace's gitignored scratch dir (host-seeded, zero git footprint) yet stays scannable by the spec tools — the home for every temp doc, never committed. This file is the one artifact — update it live as decisions land; don't also keep a separate scratch doc. This works even in a project with no existing spec graph: a `task-spec` only needs frontmatter `id` and `type` to be a valid spec, no pre-existing graph required — don't skip this step just because nothing else in the project is specced yet. 4. **Clarify.** Ask what you need via `ask_user_question`, composing rounds per the **asking-user-questions** concept skill — read it before the first round. Resolve a full round, update the task-spec with what you learned, and only open a new round if the answers raised a genuinely new question. Per that concept's degradation norms, skipped questions or a host with no UI are not blockers: record your best-guess assumptions in the task-spec, explicitly marked unconfirmed, and continue. 5. **Propose approaches.** Once the ask is clear, write 2-3 approaches into the task-spec with trade-offs and a recommendation. When approaches are easiest to compare side by side, ask via a single-select `ask_user_question` with each approach as an option (label = approach name, description = its trade-off) instead of prose alone. 6. **Present the design.** Write it into the task-spec in sections scaled to their complexity; confirm with the user as each section lands, not only at the end. 7. **Self-review.** Before asking for final sign-off, reread the task-spec for: placeholders/TBDs, sections that contradict each other, scope that's actually multiple task-specs, and ambiguous requirements — fix what you find, don't just flag it. 8. **Promote.** When the design settles a boundary, contract, or decision that belongs in a durable spec, fold it into the relevant module's `SPEC.md` now — `spec_create` for a new module, `spec_update` for its frontmatter (draft → active as it firms up), `edit` for prose. Run `spec_validate` after structural changes. 9. **Final review, then build.** Ask the user to review the (now-promoted) design once more. Once approved, implement directly against it — there is no separate plan-writing step here. Before handing off, self-review the implementation diff the way step 7 reviewed the spec: no silent lint/type suppressions (a gate error is a design signal — question the flagged state or dependency before guarding it; any genuinely-needed suppression gets explicit user sign-off first), no nontrivial derivation duplicated across files (centralize it), no rationale left as code comments (near-zero comments: decisions and invariants go to the owning spec per the writing-specs bar; only lint directives and rare one-line hazard notes survive), and when the change replaced a pattern, sweep the repo for remnants of the old one. Keep the task-spec and the durable specs honest as the code lands, and retire the task-spec once **the work itself** is done, not merely once the design was promoted.
## What a good task-spec looks like
- Scoped to one piece of work — if it's accreting unrelated decisions, split it. - States the request, the decision(s) made and why, the approaches considered and why they were or weren't picked, and anything the user explicitly deferred or declined to answer. - Gets promoted, not copied: once a decision belongs in a module's `SPEC.md`, move it there and reference it from the task-spec rather than keeping two copies that can drift.
Detail teknis
- Versi
- 1.0.0
- Lisensi
- Apache-2.0
- Pembaruan terakhir
- 24 Agu 2026
- Diterbitkan
- 24 Agu 2026
Ringkasan keputusan
Kandidat cadangan
recent repository activity
Audit
Tinjauan pemasangan
Tinjauan pemasangan dan adopsi
- Keamanan
- 86/100
- Pemeliharaan
- 100/100
- Pasang
- 92/100
Bukti tervalidasi Agent
Bukti tervalidasi Agent
Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.
- Tingkat sukses
- —
- Kegagalan terbaru
- —
- Hasil
- 0
- Kualitas output
- —
- Gagal
- 0
- Tidak relevan
- 0
- Pemasangan
- 0
- Diblokir risiko
- 0
- Perlu penyiapan
- 0
- Produksi
- 0
Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.
Pasang
Tambahkan ke alur Agent
Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.
Siklus pertumbuhan
Kit berbagi
Draf berbasis skenario untuk brainstorming, siap untuk posting manual di X.
A practical pick for design or creative work: brainstorming: Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a... 38 stars https://www.openagentskill.com/skills/jetbrains-brainstorming?ref=x
Balasan opsional dengan perintah pemasangan
Listing + install path for brainstorming: https://www.openagentskill.com/skills/jetbrains-brainstorming?ref=x Install: npx skills add JetBrains/thinkrail --skill brainstorming
Sumber listing
Diindeks Registry
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- JetBrains
- Sumber
- JetBrains/thinkrail
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
Klaim skill iniKlaim pemilik
Klaim listing skill ini
Listing Diindeks Registry ini dikaitkan dengan JetBrains, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.
Kit backlink kreator
Tambahkan badge bukti ke README Anda
Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.
[](https://www.openagentskill.com/skills/jetbrains-brainstorming)
[](https://www.openagentskill.com/skills/jetbrains-brainstorming)
[](https://www.openagentskill.com/skills/jetbrains-brainstorming/audit)
[](https://www.openagentskill.com/skills/jetbrains-brainstorming)Penulis
JetBrains
@jetbrains
Tag
Kecocokan platform
Sinyal kesehatan
- Star GitHub
- 38
- Skor kualitas
- 34/100
- Push GitHub terakhir
- 24 Agu 2026
- Petunjuk framework
- Tidak diketahui
- Tampilan OpenAgentSkill
- 0
- Salinan pemasangan
- 0
- Klik keluar
- 0
Sinyal komunitas
Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.
Kepercayaan & keamanan
Hanya sandbox
- Adopsi GitHub38 star GitHubPeriksa
- Aktivitas star/fork38 star dan 8 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
- Pemeliharaan terbaruDiperbarui hari iniLulus
- Kejelasan lisensiApache-2.0Lulus
- Kelengkapan README/SKILL.mdMetadata publik memerlukan konteks README/SKILL.md yang lebih kuatInfo
- Risiko dependensi/runtimeTidak ada petunjuk risiko dependensi besar dalam metadata publikLulus
Skill terkait
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