Skill

Score and sync AI-readiness context across dev tools

A skill for reaching 100% AI-readiness fast via the .faf context format - auto-detected stack plus a goal sentence.

Works with githubclaudecursorgemininpm

76
Spark score
out of 100
Updated 27 days ago
Version archive/skills-28-pr
Models
universal

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Why it matters

Prepare your codebase for AI-assisted development by auto-detecting stack details, filling project context to 100% completeness, and syncing that context to Claude, Cursor, and Gemini so the AI starts every session already knowing your project.

Outcomes

What it gets done

01

Auto-detect language, stack, and dependencies from your repository

02

Generate a scored AI-readiness report showing which context slots are empty

03

Guide you through filling only the gaps the AI couldn't derive itself

04

Sync completed context to CLAUDE.md, AGENTS.md, and other AI tool configs

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-faf-context | bash

Overview

FAF Context - Give the AI What It Needs

This skill gets a project to 100% AI-readiness via the .faf context format: auto-detecting the stack, seeding context from one goal sentence, and answering the remaining gaps. Use it for the fastest, minimal-typing path to 100% AI-readiness. For done-for-you use faf-wizard; to master the format use faf-expert.

What it does

A skill for getting a project to 100% AI-readiness using .faf, an IANA-registered context format (application/vnd.faf+yaml) - a typed, portable, vendor-neutral file readable by any AI. faf-cli defines 21 context slots; the flow is three steps, only the last needs the user: the project's app type determines which slots are required (a CLI needs different slots than a full-stack web app, and irrelevant slots are marked slotignored and dropped from the denominator); faf auto detects the stack and language and seeds who/what/where from a written goal sentence; whatever's left empty (usually why and when, the "purely yours" Ws) is filled by answering the AI's questions. The six Ws are terse 3-4 word labels, not prose: who (audience), what (the thing being built), why (its reason to exist), where (where it runs/ships), when (timeline/stage), and how (how it's built) - who/what/where get seeded from the goal sentence and how gets sourced from stack detection, leaving why and when as the two typically hand-written answers. The fastest path is five commands: faf auto detects the stack and seeds context from the README, faf score shows the current percentage and which slots are empty, faf go guides confirming seeded Ws and filling the 1-2 remaining, faf score again confirms 100%, and faf sync optionally pushes context into CLAUDE.md or AGENTS.md. The honesty rule underpins all of it: the AI only seeds facts the goal sentence or README literally state, never invents or templates, and leaves anything it can't source empty rather than guessing - empty beats wrong.

When to use - and when NOT to

Use this skill when you need your project at 100% AI-readiness fast, with minimum typing and maximum auto-detected context - it's the builder's quickstart path, feeding into faf-expert for depth. For a fully done-for-you one-click path use faf-wizard instead; to master the format's scoring internals, MCP config, and bi-sync use faf-expert instead; for driving a repo end-to-end with an agent use faf-go or faf-loop.

Inputs and outputs

Input is one sharp, specific goal sentence (e.g. "A CLI that scores any repo's AI-readiness and syncs context to Claude, Cursor, and Gemini - for solo developers") plus answers to the 1-2 Ws the AI couldn't derive. Output is a completed .faf context file scored 0-100%, with irrelevant slots marked slotignored and excluded from scoring.

Integrations

faf auto
faf score
faf go
faf score
faf sync

Produces a .faf file (application/vnd.faf+yaml) that can optionally sync into CLAUDE.md or AGENTS.md via faf sync for AI tools that read those files directly instead of the .faf format.

Who it's for

Time-conscious builders who want their project fully AI-context-ready without manually filling out a 21-slot spec - write one good goal sentence, confirm what auto-detection already seeded, answer the couple of questions only a human can answer, and reach 100% AI-readiness. Part of the FAF skill family (faf-context, faf-wizard, faf-expert), MIT licensed.

Source README

FAF Context - Give the AI What It Needs

When to Use

Use this skill when you need get your project to 100% ✪ AI-readiness, fast - the AI auto-detects your stack and only asks for what it can't know (your goal and the human "why"). Least typing, maximum context. For time-conscious builders; feeds into faf-expert for depth.

AI writes its best code when it has your project's context. This skill helps you hand it over - fast, and to 100%.

.faf is an IANA-registered context format (application/vnd.faf+yaml) - a typed, portable file you own, readable by any AI (no bespoke manifest, no vendor lock-in). The whole point is one number: AI-readiness, 0-100%. At 100% ✪ the AI starts every session already knowing your project - no re-explaining, no guessing. This skill is the builder's path to that number: minimum typing, maximum context.

For the done-for-you one-click path, use faf-wizard. To master the format, use faf-expert. This skill is the quickstart in between.

How it works: app-type → AI fills the max → you answer the gaps

faf-cli has 21 slots. It works in three steps - and only the last one needs you:

  1. Your app type sets which slots are required. A CLI needs different slots than a full-stack web app - faf-cli right-sizes the set and slotignoreds the rest (never counted against you).
  2. The AI fills as many as it can. faf auto detects your stack + language, and a sharp goal sentence seeds who/what/where. The better your goal, the more the AI fills for you.
  3. Whatever's left empty, the AI asks you. Those are the bits only you know - usually a couple of the 6 Ws (often why and when). Answer them → 100% ✪.

So your job isn't "fill 21 boxes." It's: write one good goal, then answer the few questions the AI couldn't fill itself.

*(Teams / Enterprise tiers add more slots - monorepos, caching, versioning - but those aren't faf-cli. faf-cli is the 21.)*

You rarely type all 6 Ws - here's why

The 6 Ws are "the underivable half" - but you almost never write all six from scratch:

  • who / what / whereseeded from your goal sentence (the AI extracts the facts your goal literally states)
  • howsourced from your stack (detection knows how it's built)
  • why / whenthe only two that are purely yours

So the fast path is: write one sharp goal, confirm the seeds, fill why + when. → 100%.

"Sometimes 3 Ws is enough. Sometimes the goal alone is enough." A great goal sentence + auto-detection can carry who/what/where/how on their own - leaving you two small answers. The better your goal, the less you type.

The fastest path to 100% ✪

faf auto      # 1. AI detects your whole stack + seeds context from your README
faf score     # 2. See the number + exactly which slots are still empty
faf go        # 3. Guided fill: confirm the seeded Ws, answer the 1–2 left
faf score     # 4. 100% ✪
faf sync      # 5. Push context into CLAUDE.md / AGENTS.md (optional)

Most projects are 1 good goal sentence + 2 answers away from Trophy.

Write the ONE goal sentence (this does the heavy lifting)

The goal is the generative input - it seeds who/what/where automatically. Make it a real, specific sentence (it's also your use-case):

  • "A CLI that scores any repo's AI-readiness and syncs context to Claude, Cursor, and Gemini - for solo developers."
    → seeds what (a CLI that scores AI-readiness), where (Claude, Cursor, Gemini), who (solo developers). You'd only add why + when.
  • "A tool to improve development." → generic; seeds nothing. (Generic phrases are ignored on purpose - empty beats wrong.)

The 6 Ws - terse labels, not prose

Each W is a 3-4 word label (hard cap < 6) - a scannable spec card, not a paragraph:

W Asks Example
Who who is it for? solo developers
What what are they building? AI-readiness scorer
Why why does it exist? eliminate context re-explaining
Where where does it run/ship? npm, Homebrew
When timeline / stage? production, since 2025
How how is it built/used? Bun CLI + WASM

Slots that don't apply → slotignored

A CLI has no frontend; an API has no UI library. Mark those slotignored and they drop out of the denominator - you're scored only on slots that matter for your app type. 100% means "everything that applies is filled," not "every box checked." (faf auto and faf go handle most of this for you.)

The honesty rule (why this works)

The AI only seeds facts your goal/README literally state - never invents, never uses templates. What it can't source, it leaves empty for you. Empty beats wrong. That's why the resulting context is trustworthy: every slot is either detected, stated by you, or honestly blank.

When you're done here

  • Want it done for you, one click? → faf-wizard
  • Want to master the format (scoring internals, MCP config, bi-sync)? → faf-expert
  • Driving a repo all the way with an agent? → faf go / faf-loop

The goal: the AI is only as good as the context you give it. Answer the few things only you know - the gaps it couldn't fill itself - and it's optimized to help you at 100% ✪.

MIT · part of the FAF skill family (faf-context · faf-wizard · faf-expert)

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

FAQ

Common questions

Discussion

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