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Invest Preflight

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erikaflowers
invest-preflight

Quick reconnaissance pass on a codebase to establish project type, tech stack, structure, scale, and conventions before running deeper skills like /invest-manifest or /invest-repo-audit. Run this first on any unfamiliar repo.

Overview

Publishererikaflowers
Repositoryinvestiture
Skill nameinvest-preflight
Stars
55
Forks
9
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by erikaflowers on GitHub. Read the source before you install it.

Installation

Install the Invest Preflight AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/erikaflowers/investiture/tree/main/.claude/skills/invest-preflight
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/erikaflowers/investiture.git /tmp/investiture
mkdir -p .claude/skills
cp -r /tmp/investiture/.claude/skills/invest-preflight .claude/skills/invest-preflight
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Invest Preflight in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Invest Preflight on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Invest Preflight is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Preflight — Codebase Intake

You are performing a fast reconnaissance pass on an unfamiliar codebase. Your job is to orient yourself and the operator so that subsequent work (manifest, audit, feature work, debugging) starts from a position of understanding — not guessing.

This is a 2-minute scan, not a deep dive. Speed over completeness. You are answering: "What is this, what's it made of, how big is it, and what should I watch out for?"

Target

The codebase at $ARGUMENTS. If no argument is provided, use the current working directory.

Scan Sequence

Run these in parallel where possible.

1. Identify the project

Read whichever of these exist (check in order, stop at first match per category):

Package manifest:

  • package.json, package-lock.json or yarn.lock or pnpm-lock.yaml
  • Cargo.toml
  • pyproject.toml, setup.py, requirements.txt, Pipfile
  • go.mod
  • Gemfile
  • pom.xml, build.gradle
  • composer.json
  • *.csproj, *.sln

Entry points:

  • src/main.*, src/index.*, src/app.*, src/App.*
  • main.*, index.*, app.* at root
  • cmd/, bin/, lib/

Config files:

  • tsconfig.json, vite.config.*, webpack.config.*, next.config.*
  • netlify.toml, vercel.json, fly.toml, railway.json, Dockerfile, docker-compose.yml
  • .env.example, .env.sample

Documentation:

  • README.md, CLAUDE.md, CONTRIBUTING.md
  • docs/ directory existence

2. Measure scale

Run these commands:

bash
# File count by extension (top 10)
find . -type f -not -path '*/node_modules/*' -not -path '*/.git/*' -not -path '*/dist/*' -not -path '*/build/*' -not -path '*/target/*' -not -path '*/__pycache__/*' -not -path '*/vendor/*' | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20

# Total source file count
find . -type f -not -path '*/node_modules/*' -not -path '*/.git/*' -not -path '*/dist/*' -not -path '*/build/*' -not -path '*/target/*' -not -path '*/__pycache__/*' -not -path '*/vendor/*' | wc -l

# Directory structure (2 levels deep)
find . -maxdepth 2 -type d -not -path '*/node_modules/*' -not -path '*/.git/*' -not -path '*/dist/*' | sort

# Git activity (if git repo)
git log --oneline -10 2>/dev/null
git shortlog -sn --no-merges 2>/dev/null | head -5

3. Detect patterns

Search for indicators of:

Testing:

  • Glob for *.test.*, *.spec.*, __tests__/, tests/, test/, spec/
  • Check for test runner config: jest.config.*, vitest.config.*, pytest.ini, .rspec, Cargo.toml [dev-dependencies]

CI/CD:

  • .github/workflows/, .gitlab-ci.yml, .circleci/, Jenkinsfile, bitbucket-pipelines.yml

Linting/Formatting:

  • .eslintrc*, .prettierrc*, biome.json, .rubocop.yml, ruff.toml, .golangci.yml

Database:

  • Grep for migration directories: migrations/, db/migrate/, alembic/, prisma/
  • Grep for ORM patterns: prisma, drizzle, sequelize, sqlalchemy, activerecord, diesel
  • Check for schema files: schema.prisma, schema.sql, *.migration.*

Auth:

  • Grep for auth patterns: jwt, oauth, passport, auth0, clerk, supabase.auth, firebase.auth

State management (frontend):

  • Grep for: redux, zustand, jotai, recoil, mobx, pinia, vuex, context, useState

4. Check for hazards

Quick scan for things that will trip up subsequent work:

  • Monorepo? Check for workspaces in package.json, lerna.json, turbo.json, nx.json, pnpm-workspace.yaml
  • Multiple languages? If the file extension scan shows 3+ language types, note it
  • Generated code? Check for generated/, __generated__/, *.gen.*, codegen in config
  • Secrets in repo? Quick grep for sk-, ghp_, AKIA, -----BEGIN, common API key patterns in source files (not .env)
  • Large files? Any source file over 1000 lines: find . -type f -name '*.{js,jsx,ts,tsx,py,rb,go,rs,java}' -not -path '*/node_modules/*' | xargs wc -l 2>/dev/null | sort -rn | head -10
  • Lock file freshness? Compare lock file modification date to package manifest date

Output Format

Do NOT write a file. Output directly to the conversation in this format:

PREFLIGHT — [project name]
═══════════════════════════════════════════════════════════════

Project:      [one-line description]
Type:         [web app | API | CLI | library | monorepo | static site | mobile app | other]
Language:     [primary language(s)]
Framework:    [framework + version, or "none"]
Database:     [database + ORM, or "none detected"]
Hosting:      [detected hosting platform, or "unknown"]
Auth:         [auth approach, or "none detected"]

Scale:
  Files:      [total source file count]
  Languages:  [breakdown by extension, top 5]
  LOC:        [approximate, if easy to determine]
  Size:       [SMALL (<50 files) | MEDIUM (50-200) | LARGE (200-500) | VERY LARGE (500+)]

Structure:
  Source:     [where source code lives — src/, lib/, app/, etc.]
  Tests:      [where tests live, or "none detected"]
  Config:     [notable config files]
  Docs:       [what documentation exists]
  CI/CD:      [what CI/CD exists, or "none"]

Git:
  Branch:     [current branch]
  Recent:     [last commit date + message]
  Authors:    [top contributors, count]
  Activity:   [active | dormant | archived]

Hazards:
  [list anything that would surprise someone working in this repo]
  [monorepo structure, generated code, missing tests, secrets in code, etc.]
  [or "None detected" if clean]

Recommended next steps:
  [ ] /invest-manifest — to inventory everything
  [ ] /invest-repo-audit — to assess quality
  [ ] [other context-specific suggestions]

═══════════════════════════════════════════════════════════════

Rules

  • Fast. This should take under 2 minutes. Don't read every file — read manifests, entry points, and READMEs. Glob and grep for everything else.
  • No files written. Output to conversation only. This is context-setting, not a deliverable.
  • Flag surprises. The Hazards section is the most valuable part. If there's a 3000-line god file, a checked-in .env, a missing lock file, or a monorepo with 14 packages — say so. These are the things that will waste time if discovered later.
  • Be honest about unknowns. If you can't determine the database or auth approach from a quick scan, say "not detected" rather than guessing.
  • Suggest next steps. Based on what you found, recommend whether /invest-manifest, /invest-repo-audit, or something else is the right next move.

Frequently asked questions

What does the Invest Preflight AI skill do?

Quick reconnaissance pass on a codebase to establish project type, tech stack, structure, scale, and conventions before running deeper skills like /invest-manifest or /invest-repo-audit. Run this first on any unfamiliar repo.

Why use Invest Preflight on TypingMind?

Because you install it once and use it with any model. Invest Preflight is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Invest Preflight in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/erikaflowers/investiture/tree/main/.claude/skills/invest-preflight. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Invest Preflight?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Invest Preflight?

As many as you like. As long as a model supports skills, you can use Invest Preflight with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Invest Preflight AI skill free?

It is published on GitHub by erikaflowers. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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