pb-spec 1.1.9

Plan-Build Spec (pb-spec): A CLI tool for managing AI coding assistant skills

pb-spec — Plan-Build Spec

pb-spec is a set of Agent Skills Specification compliant AI Coding assistant workflow skill packages. It provides a structured process — plan → build — that turns natural-language requirements into well-architected, BDD-driven, tested code.

Design Philosophy

pb-spec implements the Plan-Build pattern: a Planner Agent generates design specs, and a Builder Agent executes code with verification. The core innovation is making .feature files the absolute source of truth — all design and tasks derive FROM scenarios, not the other way around.

Core Principles

Principle	Description
BDD-First	Feature scenarios are the source of truth. Design and tasks derive FROM scenarios.
RFC 2119 Constraints	Architectural constraints use MUST/SHOULD/MAY keywords — binding for the Builder.
DAG Execution	Tasks include DependsOn metadata for parallel execution of independent tasks.
Adaptive Steering	Tasks with Complexity=High route to reasoning models; Low to fast models.
Escalation Protocol	Repeated failures auto-escalate to stronger models for root-cause analysis.
Generator/Evaluator Isolation	Generator builds; Evaluator judges with fresh context — never inherits Generator state.

Installation

No manual file configuration needed. As long as your AI assistant supports the standard Agent Skills specification (Claude Code, Cursor, GitHub Copilot, OpenCode, etc.), you can install with one command.

Run in your project root:

# Install all pb-spec workflow skills at once
npx skills add longcipher/pb-spec

# Or install only the ones you need
npx skills add longcipher/pb-spec --skill pb-init
npx skills add longcipher/pb-spec --skill pb-plan
npx skills add longcipher/pb-spec --skill pb-build
npx skills add longcipher/pb-spec --skill pb-improve

(After installation, skills will be placed in .agents/skills/ or the compatible local directory for your environment, and automatically indexed by your AI.)

Quick Start

/pb-init            → audit project, write AGENTS.md snapshot
/pb-plan "<req>"    → generate design.md, tasks.md, features/*.feature
/pb-build "<feat>"  → execute via Generator/Evaluator with BDD+TDD loops
/pb-refine "<feat>" → (optional) iterate specs on Build Blocked / DCR
/pb-improve         → audit codebase, generate prioritized specs

Skills Overview

Core SDD Workflow Skills

Skill	Trigger	Output	Description
pb-init	/pb-init	AGENTS.md	Audit repo and update managed snapshot block
pb-plan	/pb-plan <requirement>	specs/<spec>/design.md + tasks.md + features/*.feature	Design + Gherkin scenarios + ordered task breakdown with RFC 2119 constraints and DAG metadata
pb-build	/pb-build <feature>	Code + tests	BDD+TDD via Generator/Evaluator with Escalation protocol and Wave-Based parallel execution (4 Invariants)
pb-refine	/pb-refine <feature>	Revised spec files	Apply feedback or Design Change Requests
pb-improve	/pb-improve	specs/<spec>/ + specs/context.md	Codebase audit → prioritized findings → pb-plan-compatible specs
pb-brainstorming	Before creative work	Design exploration	Explores intent, requirements, and design before implementation

Review/Finalization Skills

Skill	Trigger	Description
pb-code-review	Before merge	Two-axis review (Standards + Spec) + receiving decision tree
pb-branch-finalization	Work complete	Conflict resolution + integration options

Meta/Utility Skills

Skill	Trigger	Description
pb-systematic-debugging	Any bug or failure	Find root cause before attempting fixes
pb-prototype	Design validation	Build throwaway prototypes (terminal or UI) for design questions
pb-writing-skills	Creating/editing skills	Skills are code, not prose — test them
using-pb-spec	Session start	Bootstrap: establishes skill invocation discipline

Workflow

/pb-init → /pb-plan → [/pb-refine] → /pb-build
                    ↘
                    /pb-improve → specs/ → /pb-build

Supporting skills activate automatically during the workflow:

• pb-brainstorming — before /pb-plan when requirements are unclear
• pb-code-review — review cycles around /pb-build tasks
• pb-branch-finalization — finalization after /pb-build
• pb-systematic-debugging — when tasks fail repeatedly

1. /pb-init — AGENTS.md Snapshot & Safe Merge

Audits your project and writes a pb-init snapshot into AGENTS.md using managed markers:

• <!-- BEGIN PB-INIT MANAGED BLOCK -->
• <!-- END PB-INIT MANAGED BLOCK -->

Merge behavior is non-destructive: existing content outside the managed block is preserved verbatim. The snapshot includes an Architecture Decision Snapshot so later agents inherit repo-level conventions.

2. /pb-plan <requirement> — Design & Task Planning

Produces a complete feature spec:

specs/<YYYY-MM-DD-NO-feature-name>/
├── design.md    # Scalable template: 5 required + 5 optional sections
├── tasks.md     # 4-field task blocks with DAG metadata
└── features/    # Gherkin acceptance artifacts (Source of Truth)

Key capabilities:

• BDD-First: Feature scenarios written FIRST; design and tasks derive FROM scenarios
• Scalable design template: 5 required sections (Summary, Approach, Architecture Decisions, BDD/TDD Strategy, Verification) + 5 optional sections (Requirements & Goals, Architecture Overview, Data Models, Interface Contracts, Implementation Plan)
• RFC 2119 Constraints: §Architectural Constraints section with MUST/SHOULD/MAY keywords — binding for Builder
• 4-field task schema: Context:, Verification:, Status:, Scenario Coverage:
• DAG-Enabled Tasks: TaskID, DependsOn, Complexity metadata
• Behavior Traceability Matrix: Every design component maps to a Feature scenario (no scenario = remove from design)

3. /pb-refine <feature-name> — Design Iteration (Optional)

Reads user feedback or Design Change Requests and updates design.md and tasks.md. Maintains a revision history and cascades changes without overwriting completed work.

Validates 🛑 Build Blocked and 🔄 Design Change Request packets — each carrying 3 fields: Reason, Requested Change, Impact.

4. /pb-build <feature-name> — Generator/Evaluator Implementation

Implements tasks using a Generator/Evaluator dual-persona workflow with Wave-Based parallel execution (4 Invariants) and Escalation protocol:

Generator (subagent) → READY_FOR_EVAL → Evaluator (independent context) → PASS / FAIL
On PASS  → mark task DONE
On FAIL  → fresh Generator subagent → retry
On 2nd FAIL → Escalate to stronger model for root-cause analysis
On 3rd FAIL → DCR packet to /pb-refine

Key principles: BDD-First, RFC 2119 constraints BINDING, fresh context per subagent (Evaluator never inherits Generator context), escalation over thrashing, interactive (default) or --auto mode.

5. /pb-improve — Codebase Audit & Plan Generation

Audits any codebase and writes pb-plan-compatible specs for other agents to execute. Never modifies source code — only produces specs under specs/.

/pb-improve                        full audit → prioritized findings → specs
/pb-improve quick                  cheap pass: hotspots, top findings only
/pb-improve deep                   exhaustive: every package, every category
/pb-improve security               focused audit (also: perf, tests, bugs, ...)
/pb-improve branch                 audit only what the current branch changes
/pb-improve next                   feature suggestions — where to take the project
/pb-improve plan <description>     skip the audit, spec one thing
/pb-improve review-spec <feature>  critique and tighten an existing spec
/pb-improve reconcile              refresh the backlog: verify, unblock, retire

BDD-First Integration

The core innovation: .feature files are the absolute source of truth. All design and tasks derive FROM scenarios.

features/*.feature (Source of Truth) → design.md → tasks.md → /pb-build (RED→GREEN→REFACTOR)

RFC 2119 Constraints

design.md carries a §Architectural Constraints section with MUST/SHOULD/MAY keywords — binding for the Builder. Example: [C-01] Database interactions MUST use the existing ORM layer; raw SQL MUST NOT be introduced.

4-Field Task Schema

### Task 2.1: "Successful login" — User authenticates

- **TaskID:** `T1` - **DependsOn:** `None` - **Complexity:** `High`
- **Context:** Implement JWT auth guard for login endpoint. Key files: src/auth/jwt.ts, src/routes/login.ts.
- **Verification:** `behave --tags=@login_success` exits 0; `pytest tests/auth/test_jwt.py` all pass.
- **Status:** 🔴 TODO
- **Scenario Coverage:** @auth-login-success, @auth-login-invalid-credentials

Field	Required	Description
Context:	Yes	Why this task exists, what to do, key files, dependencies
Verification:	Yes	Exact command(s) + expected output proving task is done
Status:	Yes	🔴 TODO / 🟡 IN_PROGRESS / 🟢 DONE / 🔄 DCR / ⛔ OBSOLETE
Scenario Coverage:	Yes	@scenario-id list from .feature files, or N/A for non-BDD tasks

Build Blocked / DCR Packets

Both 🛑 Build Blocked and 🔄 Design Change Request packets carry 3 fields: Reason (one sentence), Requested Change (one paragraph), Impact (affected task IDs and scenario tags).

Escalation Protocol

Failure Count	Action
1	Retry with same model
2	Escalate — auto-upgrade to stronger model for root-cause analysis
3	File DCR, stop build

Verification

just format && just lint && just test && just bdd && just test-all

Supported AI Tools

Compatible with any tool supporting the agentskills.io specification: Cursor, Claude Code, GitHub Copilot / GitHub Spark, OpenCode, Gemini CLI, Codex.

License

Apache-2.0