Agentic SDLC Skill for Claude Code, Gemini CLI, Google Antigravity & Codex

agentic-sdlc is a Documentation-First SDLC protocol for AI coding agents. It supports Claude Code, Codex, Gemini CLI, Google Antigravity 2.0, Cursor/Windsurf-style project instructions, and optional devPNT governance.

Key Features

• Risk-proportional workflow: L1/L2/L3/Spike triage avoids heavyweight process for trivial work, with a symmetric Write Triggers table mapping each event to the document it produces (one event, one destination).
• Vision-guided governance: Standalone projects use ai_docs/vision/; Hybrid projects use devPNT M-VISION as the milestone north star. The Vision names its Actors — the cast a feature serves, one light line each — so UX is designed for concrete roles, not an implicit "user".
• Architect pass — capabilities before files: at L3, before listing what changes, the feature is stated as the capabilities it needs and each is ruled against the platform (EXISTS / INADEQUATE / MISSING); what is missing is designed as a component with its own contract, of which the feature is one consumer — never inlined into the feature's code path. A ## Component Map in strategic/architecture.md is the durable inventory the pass reads, so the platform is not re-derived from source every session. On a codebase the methodology arrives in late, the map's silence is treated as unread, not empty: it can never ground a MISSING verdict.
• Execution disciplines: explicit TDD (RED/GREEN/REFACTOR), systematic debugging, an L3 spec-elicitation round, and a single code-review definition wired into the workflow phases.
• Operative + comprehension guides + agent-global KB: distil user-provided indications into source-faithful operative GUIDE_*.md (source_kind: document), and let the agent autonomously author code-comprehension guides (source_kind: code) for complex components — a source-faithful mental-model map that survives across sessions, so the next session doesn't re-derive and break the component from partial understanding. Consulted before work; shared cross-project via ~/.agentic-sdlc.
• Several people, one project: the workstream registry (audit/handoff.md) is generated from one file per open workstream, so two people opening or closing two workstreams on two branches edit two different files and their merge is clean. Row-per-workstream alone was not enough — a file-global Date: header defeats row-level ownership — so the header is derived from the sources and no writer touches it. The generated view can still conflict; that conflict is resolved by re-running index, never by hand, and validate refuses CLEAN until the file matches its sources. The append-only review log gets merge=union (a built-in driver, no per-clone configuration). It all works with no VCS at all: it is files and a generator.
• Opt-in subagent execution: an approved design projects into a validated executable plan an orchestrator can drive through subagents.
• Self-activating: a SessionStart hook emits repo-sourced orientation; a deterministic self-eval battery guards the skill's own doctrine as the release gate.
• Standalone complete: works fully with local ai_docs/ without requiring devPNT.
• devPNT symbiosis: when devPNT is available, Master Plan, Action Plan, M-VISION, and governed artifacts become the authoritative planning layer, with independent fresh-context reviews of technical artifacts and diffs.
• Independent review, twice: the design is reviewed before it is implemented and the diff before the work is declared done — by somebody other than its author. Three rungs of independence (fresh-context subagent > one-shot run > a declared self-pass, legal only when the first two are unavailable), capped at 3 rounds, one log line per review, and a PASS is invalid on "found nothing" — it must state where each constraint is satisfied.
• Question discipline: a question to the user is legal only when the agent searched first and names the search with its result, and names the decision the answer unblocks. Otherwise it proceeds on a declared assumption — same evidence duty, batched, never a stream of "shall I proceed?".
• Installed support files: Claude, Codex, Gemini, and Google Antigravity receive the full skill folder, including templates.md, architect.md, guides.md, vision.md, tdd.md, debugging.md, elicitation.md, review.md, dispatch.md, routing.md, ENFORCEMENT.md, and the validator's two files, scripts/sdlc_check.py + scripts/sdlc_core.py.
• Mechanical checks: optional validator for document structure, generated feature history, stale audit areas, and protected-path gates — check, validate, index, stale, mark, gate, plan, orient, migrate.

Installation

Via npm

npm install -g @antoneeo/agentic-sdlc-skill@latest

That is enough — the package's postinstall runs the installer. If your npm blocks install scripts (--ignore-scripts, some CI/pnpm setups), run it by hand:

agentic-sdlc-install-skill

The command is on your PATH only after a global (-g) install; after a local npm i, invoke it as npx agentic-sdlc-install-skill.

The installer copies skills/agentic-sdlc-skill/ recursively into native skill locations:

• Claude Code: ~/.claude/skills/agentic-sdlc/
• Codex: ~/.codex/skills/agentic-sdlc/
• Gemini CLI: ~/.gemini/skills/agentic-sdlc/
• Google Antigravity: ~/.gemini/config/skills/agentic-sdlc/ (detected distinctly from Gemini CLI; override the home with ANTIGRAVITY_HOME)

Restart the relevant agent, or reload skills where the CLI supports it.

The global package also exposes:

agentic-sdlc-init

Run it inside a project to create ai_docs/, Vision documents, strategic docs, audit plan, and agent protocol files (AGENTS.md — also the Antigravity CLI surface, CLAUDE.md, GEMINI.md, .cursorrules).

Runtime Shape

The actual runtime skill is the folder:

skills/agentic-sdlc-skill/
├── SKILL.md
├── templates.md
├── architect.md
├── guides.md
├── vision.md
├── tdd.md
├── debugging.md
├── elicitation.md
├── review.md
├── dispatch.md
├── routing.md
├── ENFORCEMENT.md
└── scripts/
    ├── sdlc_check.py
    └── sdlc_core.py

SKILL.md is the entrypoint. Supporting files are loaded or executed only when the agent needs them.

The validator is two files: sdlc_core.py is the family's shared spine, sdlc_check.py is this lens's entry point. Copy both, or neither — the entry point is useless alone.

The family: three lenses, one spine

Same process, three fidelity disciplines — what the agent's assertions must be faithful to:

| Package | Faithful to | Unit of work | Own doctrine | |---|---|---|---| | @antoneeo/agentic-sdlc-skill | this repository's code | feature | architect.md, tdd.md, debugging.md | | @antoneeo/kb-agentic-skill | the documents you supply | topic | taxonomy.md, distillation.md, reconciliation.md | | @antoneeo/mkt-agentic-sdlc-skill | market evidence | engagement | frameworks.md, research.md |

Triage, the Vision Gate, the review gates, the guide router, question discipline and the validator spine are byte-identical across the three. Install only the one you need; when two live in the same project, routing.md decides which lens owns a given piece of work and any of the three validators gives the same verdict on the same tree.

Standalone vs Hybrid

Standalone:

• ai_docs/ is the source of truth.
• Vision, analysis, audit, handoff, test strategy, and feature history are maintained locally.

Hybrid/devPNT:

• devPNT governs M-VISION, Master Plan, Action Plan, and versioned artifacts.
• ai_docs/ remains useful as readable context, fallback, handoff, or shadow copy.
• Divergence between user request, local Vision, and devPNT M-VISION must be surfaced before implementation.

Gemini Extension Alternative

You can still install this folder as a Gemini extension:

gemini extensions install .

For native Gemini Agent Skills, the npm installer now copies the skill folder into ~/.gemini/skills/agentic-sdlc/.

Created By

Created by Antonio Pinto (GitHub).

MIT (c) 2026 Antonio Pinto.