@JetBrains

Creator · JetBrains

Last updated · Aug 24, 2026

brainstorming

REVIEW · 69Registry indexed

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

OpenAgentSkill Trust Score
69/100

Sandbox only

Quality62/100
Audit79/100
Stars38
Verified installs0

Install targets

Codex install prompt

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.

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

Scenario

Research agents

I need my agent to research a topic, compare sources, and produce a concise report.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add JetBrains/thinkrail --skill brainstorming

Maintenance

fresh

Pushed today

Risk

Needs review

Financial research output is not financial advice; require human review before any live investment decision

GitHub quality

38

62/100 Quality · 77/100 Trust

Coverage tags

ResearchResearch agentsagent-skill

Review notes

Financial research output is not financial advice; require human review before any live investment decision · Low GitHub adoption signal

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Promising
62

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
69

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
79

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

38 GitHub stars

Repo activity

38 stars, 8 forks

Maintenance

Pushed today

License

Apache-2.0

Install

npx skills add JetBrains/thinkrail --skill brainstorming

Install safety

standard package or runtime install path

Permission surface

filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Usable metadata, review docs

Risk summary

Review before production

  • 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

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

View technical data+

Suited tasks

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Search sources

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add JetBrains/thinkrail --skill brainstorming
Policy
review
Human review
yes

Trust and risk

Trust
69/100
Audit
79/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add JetBrains/thinkrail --skill brainstorming

Do not use when

  • teams that need a vendor-supported SLA
  • 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

Agent safety v2

63/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

Resolve via API

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • Financial research output is not financial advice; require human review before any live investment decision

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • 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.

Copy 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.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use brainstorming for this task. Review https://www.openagentskill.com/api/skills/jetbrains-brainstorming/install, then install with: npx skills add JetBrains/thinkrail --skill brainstorming

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Agent fit

61/100

Research agents

Platforms

Claude Code

Audit report

Needs review · 79/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Research agents

Prototype with this skill first; keep a fallback candidate ready.

61
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

Research agents

Trust label

Prototype first

Install path

Command ready

Use when

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 62/100 quality profile

review first

  • Low GitHub adoption signal
  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one Research agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

69
OpenAgentSkill Trust Score

GitHub adoption

CHECK

38 GitHub stars

Stars/forks activity

CHECK

38 stars, 8 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

Apache-2.0

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • 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
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

62
GitHub stars
38
Freshness
Today
Install ready
Yes
License
Apache-2.0
Review before install: Low GitHub adoption signal

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- 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.

Technical details

Version
1.0.0
License
Apache-2.0
Last updated
Aug 24, 2026
Published
Aug 24, 2026

Decision snapshot

Fallback candidate

61
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

79
Needs review
Security
86/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for brainstorming, ready for a manual X post.

Curator note
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
Open X draft
Optional reply with install command
Listing + install path for brainstorming:
https://www.openagentskill.com/skills/jetbrains-brainstorming?ref=x

Install: npx skills add JetBrains/thinkrail --skill brainstorming

Listing source

Registry indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
JetBrains
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This Registry indexed listing is attributed to JetBrains but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

Add the evidence badges to your README

Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/jetbrains-brainstorming?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jetbrains-brainstorming)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/jetbrains-brainstorming?metric=trust&label=Trust)](https://www.openagentskill.com/skills/jetbrains-brainstorming)
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[![Agent Proven](https://www.openagentskill.com/api/badge/jetbrains-brainstorming?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/jetbrains-brainstorming)

Author

J

JetBrains

@jetbrains

Platform fit

Health signals

GitHub stars
38
Quality score
34/100
Last GitHub push
Aug 24, 2026
Framework hints
Unknown
OpenAgentSkill views
0
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Sandbox only

69
  • GitHub adoption38 GitHub starsCHECK
  • Stars/forks activity38 stars, 8 forks; issue activity unavailable in current metadataCHECK
  • Recent maintenancePushed todayPASS
  • License clarityApache-2.0PASS
  • README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
  • Dependency/runtime riskno major dependency risk hints in public metadataPASS