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ai-first-engineering

Skill2 starsChanged 28 days agoApache-2.0View on GitHub

Decomposes ambiguous software requirements into deterministic milestones, executable acceptance criteria, and test-backed delivery pipelines for AI agent development.

19 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 9 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 17 edited versions we read keep these.

  • 9

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never write production code based on vague requirements.

    line 15
  2. Distinctive:

    Every modification must be coupled with automated validation (unit tests, integration suites, linters, or visual browser assertions).

    line 21
  3. Distinctive:

    If tests fail, diagnose the root cause from the error log before modifying code.

    line 22
  4. Distinctive:

    When given an ambiguous task (e.g., *"Make user onboarding faster"* or *"Add subscription billing"*), follow this three-stage breakdown:

    line 28
  5. Distinctive:

    Before modifying core abstractions, evaluate the Risk Radius:

    line 51
  6. Distinctive:

    When encountering unexpected test failures or runtime regressions:

    line 63
  7. Distinctive:

    Read Full Error Trace: Never guess or apply speculative patches without inspecting the actual stack trace.

    line 65
  8. Distinctive:

    Reproduce in Isolation: Create a minimal reproduction test or script before touching implementation files.

    line 66
  9. Distinctive:

    Binary Search (Bisect): If behavior unexpectedly changed, identify the breaking commit or input change systematically.

    line 67

“Common” is measured: kept by at least 6 in 10 of the 17 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

AI-First Engineering Principles & Delivery Playbook

This skill establishes best practices for orchestrating high-velocity software engineering tasks with AI agents. It bridges the gap between human product intent and deterministic, zero-hallucination agent execution.

1. Core Directives

  1. Deterministic Specification Before Code:
    • Never write production code based on vague requirements.
    • Deconstruct high-level prompts into verifiable acceptance criteria (Given/When/Then).
  2. Blast Radius Minimization:
    • Scope code modifications strictly to the files necessary to satisfy the feature.
    • Guard against accidental refactoring of unrelated subsystems or styles.
  3. Continuous Verification Loop:
    • Every modification must be coupled with automated validation (unit tests, integration suites, linters, or visual browser assertions).
    • If tests fail, diagnose the root cause from the error log before modifying code.

2. Requirement Decomposition Matrix

When given an ambiguous task (e.g., "Make user onboarding faster" or "Add subscription billing"), follow this three-stage breakdown:

[Ambiguous Goal] ──► [Milestone Decomposition] ──► [Executable Criteria] ──► [Zero-Regression Delivery]

Stage 1: Milestone Decomposition

Break large tasks into discrete, independently testable phases:

  • Phase 1: Contracts & Schema: Types, interfaces, database schemas, and API contracts.
  • Phase 2: Failing Assertions (Red): Unit / integration tests validating expected behavior.
  • Phase 3: Implementation (Green): Minimal surgical code satisfying the tests.
  • Phase 4: Hardening & Docs (Refactor): Error handling, edge cases, logging, and documentation.

Stage 2: Executable Acceptance Criteria

Formulate specifications using the standard Gherkin / BDD structure:

  • Given: Initial system state and prerequisites.
  • When: Specific user or API action occurs.
  • Then: Measurable system response, database state, or error envelope.

3. Risk Radius & Boundary Containment

Before modifying core abstractions, evaluate the Risk Radius:

Radius TierScopeRequired Precautions
Tier 1: Leaf NodeIsolated helper functions, standalone componentsStandard unit test verification
Tier 2: Service / StoreState management, database queries, shared servicesIntegration tests + typechecking
Tier 3: Core AbstractionDB migrations, auth middleware, global configMigration rollback plan + full test suite run

4. Autonomous Debugging Protocol

When encountering unexpected test failures or runtime regressions:

  1. Read Full Error Trace: Never guess or apply speculative patches without inspecting the actual stack trace.
  2. Reproduce in Isolation: Create a minimal reproduction test or script before touching implementation files.
  3. Binary Search (Bisect): If behavior unexpectedly changed, identify the breaking commit or input change systematically.
  4. Surgical Fix: Apply the smallest possible fix that resolves the issue while preserving surrounding code formatting and comments.

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