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Agent skill

Init Project Light

by flonat in flonat/flonat-research

Bootstrap a lightweight project with minimal guidance, context, and repository structure.

MITAuto-check passedDevelopment

Install Init Project Light

skills CLI
$ npx skills add flonat/flonat-research --skill init-project-light -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install flonat/flonat-research init-project-light --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/flonat/flonat-research.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/init-project-light .claude/skills/init-project-light && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
init-project-light
GitHub stars
145
Token cost
~1.1k tokens
SKILL.md length
454 words
Files
1
Skills in repo
83
Repo updated
First seen
Licence
MIT

At a glance

Bootstrap a lightweight project with minimal guidance, context, and repository structure.

  • Works in 5 steps: Scan → Interview (2-3 questions max) → Create CLAUDE.md → …
  • A small non-research project needs durable AI collaboration without the full research
  • SKILL.md covers When to Use, When NOT to Use — Escalate to…, Phase 1: Scan and Phase 2: Interview (2-3…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Init Project Light is an agent skill from flonat/flonat-research. Bootstrap a lightweight project with minimal guidance, context, and repository structure. Use when a small non-research project needs durable AI collaboration without the full research or course scaffold. Not for formal research projects; use $init-project-research.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Project scaffolding. The repository describes itself as: Shareable Claude Code + Codex infrastructure for PhD researchers — skills, agents, hooks, and rules for academic workflows. The licence is MIT.

When your agent uses it

  • A small non-research project needs durable AI collaboration without the full research
  • Course scaffold

Example prompts

  • “/init-project-light”

Requirements

  • Pre-approved tools (allowed-tools): Bash(mkdir*), Bash(ls*), Bash(touch*), Read, Write, Edit, Glob, Grep, AskUserQuestion

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Scan
  2. Interview (2-3 questions max)
  3. Create CLAUDE.md
  4. Organise (suggest, don't force)
  5. Confirmation

What it can do on your machine

Read from SKILL.md and the folder at commit da27600. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash(mkdir*)
    • Bash(ls*)
    • Bash(touch*)
    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • AskUserQuestion

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Init Project Light loads about 1.1k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 454 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from flonat/flonat-research at commit da27600, republished under its MIT licence (© flonat). 454 words, ~1,112 tokens.

Download SKILL.mdSave it as .claude/skills/init-project-light/SKILL.md (or your agent's skills folder).
name
init-project-light
description
Bootstrap a lightweight project with minimal guidance, context, and repository structure. Use when a small non-research project needs durable AI collaboration without the full research or course scaffold. Not for formal research projects; use $init-project-research.
allowed-tools
Bash(mkdir*), Bash(ls*), Bash(touch*), Read, Write, Edit, Glob, Grep, AskUserQuestion
argument-hint
[no arguments — runs in current directory]

Init Project Light

Lightweight project bootstrapper for small projects that do not need a full research-project scaffold.

When to Use

  • Small document collections (proposals, applications, meeting notes)
  • One-off or short-lived projects
  • Projects without a code pipeline or Overleaf link
  • When the user says "set up something light", "quick init", "organise this folder"
  • Any project that does not warrant the installation's full research-project initializer

When NOT to Use — Escalate to a full research-project initializer

  • Research papers targeting a journal or conference
  • Projects with code, data, or computational pipelines
  • Anything that needs Overleaf, git, or a vault atlas entry

Phase 1: Scan

Read everything already in the directory before asking questions.

  1. List all files and folders (excluding .claude/, .DS_Store)
  2. Read text files (.md, .tex, .bib, .txt) to understand content — respect file size (skip files > 500 lines, note them)
  3. Build a mental model: what is this project, what's the main output, who's involved?

Goal: Minimise interview questions by inferring answers from existing files.

Phase 2: Interview (2-3 questions max)

Use the available structured-question mechanism. Only ask what you couldn't infer from Phase 1.

Pick from these (skip any you can already answer):

  1. What is this project? — one sentence (e.g., "PhD research proposal for [University]")
  2. What's the main output? — document, application, collection of notes, etc.
  3. Anyone else involved? — names and roles if relevant

If Phase 1 gave you enough, confirm your understanding instead of asking:

"From the files, this looks like [X]. The main output is [Y]. Correct?"

Show full SKILL.md (204 more words)Show less

Phase 3: Create CLAUDE.md

Follow the lean-guidance-files rule. Include only:

  1. Project overview — 2-3 sentences from interview/scan
  2. People — if collaborators/supervisors exist
  3. Directory structure — compact tree of what exists
  4. Conventions — only if detectable (e.g., LaTeX compilation, bibliography style)
  5. Key context — anything a future session needs to know immediately

Do NOT include:

  • Detailed literature notes or reference lists
  • Action items or timelines (those go to vault)
  • Anything that duplicates global rules

Phase 4: Organise (suggest, don't force)

Based on what's in the directory, suggest lightweight organisation. Present options and wait for approval.

Standard suggestions
FolderWhen to suggest
to-sort/Multiple unsorted documents exist
docs/Reference materials, guidelines, or background reading present
archive/Old versions or abandoned drafts detected
Rules
  • Never create more than 2-3 folders — this is a light project
  • Never move files without explicit approval
  • If the existing structure already makes sense, say so and skip this phase
  • If there's a .claude/settings.local.json, leave it. If not, create one with standard permissions.
Standard permissions (.claude/settings.local.json)
json
{
  "permissions": {
    "allow": [
      "Bash(latexmk *)",
      "Bash(ls:*)",
      "Bash(mkdir:*)",
      "Bash(tree:*)",
      "Edit",
      "Glob",
      "Grep",
      "Read",
      "Write"
    ],
    "deny": []
  }
}

Only create if missing. Never overwrite existing permissions.

Phase 5: Confirmation

Short report:

Set up lightweight project: <name>

Created:
  - CLAUDE.md
  - [any folders created]
  - [.claude/settings.local.json if created]

Skipped (use an installed full research-project initializer if needed later):
  - Git, Overleaf, vault atlas, code scaffold

Cross-References

SkillRelationship
Installed full research-project initializerEscalate to this for full research projects
update-project-docRun later to refresh CLAUDE.md if the project grows

© flonat, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/init-project-light of flonat/flonat-research.

Open the folder on GitHubat commit da27600

Compare with similar skills

Init Project Light next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Init Project Light this skillflonat/flonat-research145—~1.1kAutomated safety check: PassMIT
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PonytailDavidObando/gsharp5648 repos~1.7kAutomated safety check: PassMIT
Run Nx Generatornrwl/nx29k2 repos~592Automated safety check: NotesMIT
Conductor Setupgemini-cli-extensions/conductor3.8k—~4.2kAutomated safety check: PassApache-2.0
Mirage VFS Adapter Authoringstrukto-ai/mirage3.7k—~2.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Init Project Light

What does Init Project Light do?

Bootstrap a lightweight project with minimal guidance, context, and repository structure. Init Project Light is an agent skill from flonat/flonat-research. Bootstrap a lightweight project with minimal guidance, context, and repository structure.

When should I use Init Project Light?

Init Project Light fits situations like: A small non-research project needs durable AI collaboration without the full research; course scaffold.

How do I install Init Project Light in Claude Code?

Run `npx skills add flonat/flonat-research --skill init-project-light -a claude-code`. Or copy the skill folder (skills/init-project-light in flonat/flonat-research) into .claude/skills/init-project-light in your project. Claude Code loads it when a task matches its description.

How do I install Init Project Light in Codex?

Run `npx skills add flonat/flonat-research --skill init-project-light -a codex`. Or copy the skill folder (skills/init-project-light in flonat/flonat-research) into .agents/skills/init-project-light in your project. Codex loads it when a task matches its description.

Can I use Init Project Light in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add flonat/flonat-research --skill init-project-light -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/init-project-light, .gemini/skills/init-project-light, .github/skills/init-project-light and .opencode/skills/init-project-light in your project.

What does Init Project Light need to run?

SKILL.md names no scripts, command-line tools or credentials: Init Project Light is instructions for the agent only. Its frontmatter pre-approves these tools: Bash(mkdir*), Bash(ls*), Bash(touch*), Read, Write, Edit, Glob, Grep, AskUserQuestion.

Does Init Project Light access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Init Project Light safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Init Project Light use?

Init Project Light is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Init Project Light use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Init Project Light?

Skills that share tags, products or a category with Init Project Light: Nx Generate (nomcopter/react-mosaic, 4.8k stars), Ponytail (DavidObando/gsharp, 564 stars), Run Nx Generator (nrwl/nx, 29k stars) and Conductor Setup (gemini-cli-extensions/conductor, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Init Project Light?

flonat (a GitHub user) maintains it in flonat/flonat-research, which has 145 GitHub stars. The repository holds 83 skills in this directory. The repository was last updated on September 29, 2026.

Source: flonat/flonat-research on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.