@JetBrains

Creator · JetBrains

Last updated · Aug 24, 2026

starting-a-new-project

REVIEW · 66Registry indexed

Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instea

OpenAgentSkill Trust Score
66/100

Sandbox only

Quality63/100
Audit78/100
Stars38
Verified installs0

Install targets

Codex install prompt

Install the "starting-a-new-project" agent skill from https://github.com/JetBrains/thinkrail/tree/main/packages/pi-thinkrail-workflow/skills/starting-a-new-project. 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 when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead. 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-starting-a-new-project","task":"Install starting-a-new-project","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

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Agent fit

Claude Code + CLI + Codex

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

Install

Ready

npx skills add JetBrains/thinkrail --skill starting-a-new-project

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

63/100 Quality · 74/100 Trust

Coverage tags

ResearchRAG and knowledgecoding-agentsagent-skill

Review notes

Financial research output is not financial advice; require human review before any live investment decision · The skill references external concept skills (writing-specs, asking-user-questions) that are not included in the submission. This may cause runtime failures if those skills are not available in the agent environment.

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
63

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
66

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

Audit

Needs review
78

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 starting-a-new-project

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

  • The skill references external concept skills (writing-specs, asking-user-questions) that are not included in the submission. This may cause runtime failures if those skills are not available in the agent environment.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Low GitHub adoption signal
  • Quality score needs review

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

  • Coding agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Inspect source files

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add JetBrains/thinkrail --skill starting-a-new-project
Policy
review
Human review
yes

Trust and risk

Trust
66/100
Audit
78/100
Risk level
Needs review

Outcome loop

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

Install command

npx skills add JetBrains/thinkrail --skill starting-a-new-project

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • The skill references external concept skills (writing-specs, asking-user-questions) that are not included in the submission. This may cause runtime failures if those skills are not available in the agent environment.
  • No OpenAgentSkill engagement data yet

Agent safety v2

62/100 · 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 starting-a-new-project in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20starting-a-new-project%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jetbrains-starting-a-new-project/install
Install command: npx skills add JetBrains/thinkrail --skill starting-a-new-project
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 starting-a-new-project for this task. Review https://www.openagentskill.com/api/skills/jetbrains-starting-a-new-project/install, then install with: npx skills add JetBrains/thinkrail --skill starting-a-new-project

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

62/100

Coding agents

Platforms

Claude Code

Audit report

Needs review · 78/100

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

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Coding agents

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

62
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

Coding agents

Trust label

Prototype first

Install path

Command ready

Use when

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

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 63/100 quality profile

review first

  • Low GitHub adoption signal
  • The skill references external concept skills (writing-specs, asking-user-questions) that are not included in the submission. This may cause runtime failures if those skills are not available in the agent environment.
  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one Coding 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.

66
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

  • The skill references external concept skills (writing-specs, asking-user-questions) that are not included in the submission. This may cause runtime failures if those skills are not available in the agent environment.
  • 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.

63
GitHub stars
38
Freshness
Today
Install ready
Yes
License
Apache-2.0
Review before install: Low GitHub adoption signal · The skill references external concept skills (writing-specs, asking-user-questions) that are not included in the submission. This may cause runtime failures if those skills are not available in the agent environment.

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: starting-a-new-project description: "Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead." ---

# Starting a new project

The workspace is empty: no code, no decisions. Turn the user's idea into one clear, buildable document — `goal-and-requirements.md` — then hand off to `brainstorming` for the features that follow.

**Hold the writing-specs bar.** Read that concept skill before saving anything — it carries the short / honest / on-rails rules every section you save must meet.

## Method

1. **Build on what's already said.** Never re-ask what the request already told you. 2. **Infer, then confirm** — propose a concrete draft and let the user correct it; a suggestion beats an open question. Compose `ask_user_question` rounds per the **asking-user-questions** concept skill (read it before the first round — it carries the option, confirmation, and degradation norms). 3. **MVP first.** The right v1 is smaller than the user expects. Every v1 capability must justify itself. 4. **Save incrementally.** Create the file as soon as the first section is settled, then add each confirmed section in template order. Don't batch; don't invent unconfirmed content. 5. A skipped question is not a blocker — proceed on the current model and note real gaps inline.

## Working model (infer from the request; never ask these directly)

``` audience: personal | public | both domain: what space this is in tech: stack mentioned, or null scope: small | large depth: light | standard | full creator_is_user: does the maker use it? ```

`depth` scales the document: `light` = a one-liner idea → a few lines; `full` = named competitors / multiple user types → a full PRD. It can only grow during the conversation, never shrink.

## Fast path — pre-filled brief

If the request already reads like a spec (several headings or a multi-section brief), parse it, treat those sections as **confirmed**, save them immediately, and only pursue what's genuinely missing and required by `depth`. Don't ask the user to confirm what they already wrote. The one always-offered extra is alternatives research (below).

## Flow

1. **Orient** — one line: "Let's nail the goal and scope, then I'll save it as `goal-and-requirements.md`." 2. **Overview** — infer it (`depth`-sized: a sentence → a paragraph naming what it replaces) and confirm. 3. **Problem** — one tailored question referencing the domain (never generic); turn the answer into a statement (who / what they do today / the specific breakdown) and confirm. Skip if the Overview already implies it. 4. **Route** from the model — don't ask "who's this for" unless genuinely ambiguous: personal / first-person pain / `depth=light` → **Personal spec**; public / named users / `depth=full` → **PRD**. 5. **Elicit the branch's sections** (below), inferring and confirming each, saving as you go. 6. **Research alternatives** (always offered, never forced): `web_search` + `fetch_content` for the closest open-source projects / products, then offer to add an **Alternatives Considered** section (name, one-line gap, URL). On a pre-filled brief, ask permission first. 7. **Review** the full draft in plain markdown and confirm, then finalize.

### Personal spec (sections)

`# Title` + one-line tagline · **Overview** · **Problem** · **V1 Features** (only capabilities the tool is useless without) · **Tech Notes** (stack, or TBD).

### PRD (sections)

`# Title` + tagline · **Overview** · **Problem Statement** · **Target Users** (roles, not demographics) · **Jobs to Be Done** ("When [situation], I want [motivation], so I can [outcome]") · **Key User Story** (one concrete scenario) · **Goals** (verb-first, measurable) · **Non-Goals** · **Success Metrics** / **Done Conditions** · **MVP Scope** (`In v1` — each item justified against a Goal/Success condition; `Out of v1`) · **Non-Functional Requirements** (only if they exist) · **Technology** (Aspect | Choice | Rationale).

Skip any section the model already answers or that `depth` doesn't warrant (`light` → skip Goals/NFRs, binary Done Conditions instead of metrics). Reject vague goals inline: "'Better UX' isn't a goal — 'first result in under 30s' is."

## Saving

- `spec_create` once, `path: "goal-and-requirements.md"`, a slug `id`, `type: "goal-and-requirements"`, `title`, `status: "draft"`; replace the scaffold with the chosen template + the sections settled so far. - `edit` to add each confirmed section in template order. - `spec_update` `status: draft → done` once finalized.

## Next

State plainly that the spec is saved. Suggest the natural next step — sketch `architecture.md`, then use `brainstorming` per feature. There is no board/ticket hand-off — say it and stop: **this workflow ends here**; feature work from now on routes through choosing-a-workflow → `brainstorming`.

Technical details

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

Decision snapshot

Fallback candidate

62
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

78
Needs review
Security
80/100
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 starting-a-new-project, ready for a manual X post.

Curator note
starting-a-new-project: Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new...

38 stars

https://www.openagentskill.com/skills/jetbrains-starting-a-new-project?ref=x
Open X draft
Optional reply with install command
Listing + install path for starting-a-new-project:
https://www.openagentskill.com/skills/jetbrains-starting-a-new-project?ref=x

Install: npx skills add JetBrains/thinkrail --skill starting-a-new-project

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-starting-a-new-project?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jetbrains-starting-a-new-project)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/jetbrains-starting-a-new-project?metric=trust&label=Trust)](https://www.openagentskill.com/skills/jetbrains-starting-a-new-project)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/jetbrains-starting-a-new-project?metric=audit&label=Audit)](https://www.openagentskill.com/skills/jetbrains-starting-a-new-project/audit)
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Author

J

JetBrains

@jetbrains

Platform fit

Health signals

GitHub stars
38
Quality score
35/100
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

66
  • 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