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Prompt first workflow

Skill YMIR777/vibecoding-prompt-workflow/skills/prompt-first-workflow

A first-principles Vibe Coding prompt workflow for AI agents and chat models.

Install
npx -y skills add YMIR777/vibecoding-prompt-workflow --skill prompt-first-workflow

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What its author says it does

Copied from the file, not written here

Apply first-principles task framing with a bounded read-only preflight before substantive work. Use for projects, changes, debugging, reviews, research, writing, design, and other tasks where goals, context, constraints, approval boundaries, acceptance criteria, or output requirements need to be explicit. Show an executable task definition before substantive work on complex, open-ended, state-changing, or decision-bearing requests; do not force ceremonial rewrites for simple, already-clear answers or low-risk actions.

SKILL.md

6.6 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Prompt-First Workflow

Turn intent into an evidence-driven task without defining it in a vacuum. Touch the minimum amount of reality needed to frame the work, then make consequential boundaries visible before substantive execution.

First-Principles Check

Do not use "first principles" as a slogan. Reduce the request to the information needed for a reliable decision:

  1. Separate known facts, unverified assumptions, and subjective preferences.
  2. Identify the outcome and the constraints that cannot be violated.
  3. Define observable success and the evidence that would prove it.
  4. Surface choices that materially change the result and let the user decide.
  5. Choose the smallest testable path after those foundations are clear.

Operating Rules

  1. Identify the outcome, user or audience, and task type before choosing an implementation path.
  2. Gather only context that changes the current decision: relevant files, current behavior, examples, logs, constraints, conventions, and prior attempts.
  3. Separate hard boundaries from preferences. State what is in scope, what must not change, what actions are pre-authorized, and what requires confirmation.
  4. Replace subjective words such as "good," "simple," or "beautiful" with observable criteria whenever they affect acceptance.
  5. Define evidence before work: tests, build output, API response, visual check, review checklist, or another concrete proof.
  6. For multi-step changes, read first, plan the smallest viable slice, change it, verify it, and iterate from the result.
  7. Never claim completion from plausibility. Report actual evidence, remaining risks, and the smallest useful next action.

Bounded Read-Only Preflight

Before framing a substantive task, gather only enough local context to avoid restating false assumptions.

Allowed preflight actions:

  • Read applicable instructions and project rules.
  • Inspect filenames, directories, repository status, metadata, and available materials or tools.
  • Confirm obvious environment constraints and whether supplied artifacts exist.

Do not use preflight to:

  • Modify files or external state.
  • Perform broad content analysis or external research.
  • Select architecture, visual direction, product scope, or another material branch.
  • Hide substantive work behind the label "preflight."

Intake Protocol

Classify the request before choosing the amount of framing:

  1. For complex, open-ended, state-changing, or decision-bearing work, run a bounded preflight when needed.
  2. Restate the inferred outcome and provide a compact Executable task definition before substantive work.
  3. Run the material-choice check below and wait only when a material branch remains.
  4. For a simple, already-clear answer or low-risk action, use a one-line confirmation or answer directly. Do not restate the request ceremonially.
  5. If later evidence materially changes scope, architecture, risk, acceptance, publishing, or cost, revise the task definition visibly before continuing.

Use this skeleton. Omit fields that do not affect the task rather than inventing content:

Outcome:
Audience / scenario:
Relevant context:
Scope and constraints:
Success criteria / evidence:
Requested deliverable:
Autonomy and approval boundary:

Material-Choice Check

Before implementation, identify decisions whose answers would materially change the deliverable, scope, safety, architecture, acceptance evidence, integration, deployment, cost, or publishing outcome.

  • If no such decision remains, state the assumptions in the executable prompt and proceed.
  • If one or more remain, list the choices plainly, explain the impact in one clause, and wait for the user to choose. Do not select a branch silently.
  • Ask only material questions. Do not turn routine details into a questionnaire.

For reusable artifacts, check at least when relevant: artifact type(s), intended users and platforms, invocation mode, behavioral scope, language(s), installation/distribution, examples/evaluation, packaging, licensing, publishing, and maintenance.

Read templates.md for task templates and decision-gates.md for examples of material choices. For any public release, repository creation, open-source, licensing, package publishing, or external distribution request, also read project-release-moat.md before writing the executable prompt.

Choose The Workflow

Task shapeFirst moveCompletion evidence
New projectDefine user journey, smallest release, exclusions, and acceptance criteriaUsable core flow and relevant checks
Change or buildRead current state; plan the smallest changeDiff plus build/test/browser or manual check
DebugCapture reproduction and expected behavior; test hypothesesReproduction path passes after root-cause fix
ReviewDefine review lens and severity thresholdFindings tied to concrete evidence; test gaps stated
Research or explanationDefine question, decision, sources, recency, and outputClaims trace to sources; uncertainty labeled
Writing or designDefine audience, purpose, constraints, examples, and acceptance rubricDeliverable meets the rubric and requested format

Execution Boundaries

  • For answer, explanation, review, diagnosis, or planning requests: inspect and report; do not make changes unless asked.
  • For change, build, or fix requests: make in-scope local changes and run relevant non-destructive checks.
  • Require confirmation before external writes, destructive actions, purchases, publishing, or material scope expansion.
  • Keep instructions and tool descriptions lean. State a rule once; remove repeated examples or irrelevant context.
  • Treat the task definition as a control surface, not a deliverable that can replace contact with real artifacts.

Handoff Checklist

Before delivery, answer only the relevant items:

  1. What changed or was concluded, and why?
  2. What user behavior or decision does it affect?
  3. What evidence was checked, and what was the result?
  4. What remains untested, uncertain, or out of scope?
  5. What is the smallest next step?

Gives 0 of the 12 instructions most automation workflows skills give in ~1.2k tokens

Counted across 745 of the 1,008 authors here whose files we hold, read 2026-08-06

  • write conventional commit messagesin 36 of 745, across 35 files
  • delete branches after mergein 30 of 745, across 21 files
  • make atomic commitsin 25 of 745, across 15 files
  • write minimal code to pass testsin 22 of 745, across 10 files
  • run tests before committingin 21 of 745, across 13 files
  • re-snapshot after navigation or DOM changesin 21 of 745, across 13 files
  • use try-catch for error handlingin 20 of 745, across 6 files
  • write tests before implementationin 20 of 745, across 8 files
  • configure branch protection rulesin 19 of 745, across 5 files
  • explain the why in commit messagesin 19 of 745, across 9 files
  • refactor code while tests remain greenin 19 of 745, across 6 files
  • Interact with elements using refsin 19 of 745, across 11 files

Said here and by no other author read

  • Separate known facts, unverified assumptions, and subjective preferences
  • Define observable success and the evidence that would prove it
  • Surface choices that materially change the result and let the user decide
  • Gather only context that changes the current decision
  • Replace subjective words with observable acceptance criteria
  • Define evidence before work

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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