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pm-ai-toolkit

v1.3.0

Published

A Cursor plugin for Product Managers: transform FSD, BRD, PRD, Figma designs, images, and email (.eml) into features, user stories, tasks, test cases, exit criteria, and architecture diagrams with version tracking and scope analysis

Readme

PM AI Toolkit

npm version

A plugin for Cursor and Claude Code that turns raw PM inputs — FSD, BRD, PRD documents, Figma designs, images, OpenAPI specs, and email files (.eml) — into a full suite of development artifacts: requirements, features, user stories, tasks, test cases, exit criteria, architecture diagrams, sprint plans, and stakeholder updates. Built-in version tracking, scope analysis, delta detection, and rollback.

Quick Start

# Install
npx pm-ai-toolkit install

# Restart Cursor, then kick off a new project
Use pm-ai-toolkit:brainstorming
# — or, if you already have documents —
Use pm-ai-toolkit:knowledge-ingestion

What's Included

Skills (16)

| Skill | Triggers When | What It Does | |-------|---------------|--------------| | pipeline-orchestrator | PM wants to run the full pipeline end-to-end | Runs all skills in dependency order with configurable approval gates, progress tracking, and resume support via .pipeline-state.json | | status-dashboard | PM asks "what's the status?" or returns to a project | Read-only scan of all artifacts: versions, pipeline completeness, staleness warnings, and recommended next actions | | brainstorming | Starting a new initiative or exploring ideas | Guided ideation: explores approaches, clarifies requirements, produces an approved design spec, then hands off to knowledge-ingestion | | knowledge-ingestion | PM provides FSD, BRD, PRD, Figma links, images, API specs, or email files (.eml) | Parses diverse inputs (including stakeholder email threads) into a normalized requirements summary with gap analysis and RFC 2119 language normalization | | feature-extraction | After requirements are ingested | Transforms requirements into a prioritized feature list with MoSCoW classification, dependencies, and tech stack detection | | user-story-generation | After features are extracted | Converts features into user stories with personas, story points, acceptance criteria, and Definition of Ready checklist | | task-decomposition | After user stories are generated | Breaks stories into granular 2–4 hour development tasks with effort estimates and layer assignments | | test-case-generation | After tasks are decomposed | Generates unit/integration/e2e test cases with code snippets, coverage matrix, exit criteria cross-references, and optional Excel export | | exit-criteria-generation | After tasks are decomposed | Produces BDD acceptance scenarios and verification checklists per feature, cross-linked to test case IDs | | architecture-diagrams | After features are extracted | Generates Graphviz DOT or Mermaid diagrams: solution overview, technical architecture, class, sequence, and ER diagrams — with syntax validation | | scope-analyzer | Before any regeneration | Delta analysis engine: detects changes in inputs, traces downstream impact, flags possibly-removed requirements, and produces a scope delta report | | risk-register | After agent reviews or when PM raises risks | Aggregates project risks from all artifacts, scores by likelihood × impact, defines mitigations, and tracks risk lifecycle | | version-changelog | After any skill generates artifacts | Manages semantic versioning, draft/finalized lifecycle, archiving (<artifact>-v<version>.md), and master CHANGELOG.md | | sprint-planner | After user stories are generated, or when PM says "plan sprints" | Allocates stories to numbered sprints by velocity, MoSCoW priority, and capacity — with utilisation warnings and optional release milestones | | stakeholder-update | When PM needs to communicate progress | Generates status updates in exec-brief, engineering-detail, or customer-facing tone from current artifact state | | rollback | When PM needs to restore a previous finalized version | Lists archived versions, restores selected version as new draft baseline, logs to CHANGELOG, and runs scope analysis |

Agents (5)

Agents are dispatched at key pipeline gates — always optional, never forced. Each agent provides a structured review report that feeds back into the pipeline severity system (BLOCKER / WARNING / INFO).

| Agent | Dispatched After | What It Reviews | |-------|-----------------|-----------------| | spec-reviewer | Brainstorming produces a design spec | Completeness, consistency, scope, and pipeline-readiness of the spec | | requirements-analyst | Stage 1: knowledge-ingestion | Requirements for completeness, consistency, ambiguity, testability, and feasibility | | story-reviewer | Stage 3a: user-story-generation | User story quality against INVEST criteria, acceptance criteria testability, and persona alignment | | solution-architect | Stage 3b: architecture-diagrams | Architecture for soundness, scalability, security, separation of concerns, and technology fit | | task-estimator | Stage 4: task-decomposition | Effort estimates for uncertainty (Three-Point Estimation), splitting candidates, and schedule risk |


Pipeline Flow

[Entry Points]
  brainstorming ──────────────────────────────────────────────────────────┐
  knowledge-ingestion (direct entry if documents/emails are ready)          │
                                                                           │
[Stage 1] knowledge-ingestion                                             ←┘
            │  optional: spec-reviewer agent (before stage 1)
            │  optional: requirements-analyst agent (after stage 1)
            ▼
[Stage 2] feature-extraction
            ├──────────────────────────────────────────────────────────────┐
            ▼                                                               ▼
[Stage 3a] user-story-generation              [Stage 3b] architecture-diagrams
            │  optional: story-reviewer agent              │  optional: solution-architect agent
            ▼                                               ▼
[Stage 4] task-decomposition
            │  optional: task-estimator agent
            ├─────────────────────────────────────────────────────────────┐
            ▼                                                              ▼
[Stage 5a] test-case-generation         [Stage 5b] exit-criteria-generation
  (includes exit_criteria_ref)            (includes test_coverage column)
            │                                              │
            └──────────────────────┬───────────────────────┘
                                   ▼
[Stage 6] version-changelog (draft tracking after every stage)

[Optional]
  sprint-planner    ← plan sprints after user stories exist
  stakeholder-update ← generate comms at any time
  rollback          ← restore previous finalized version

[Cross-cutting — invoked automatically]
  scope-analyzer    ← runs before any regeneration to detect changes
  risk-register     ← aggregates risks from all artifacts and agent reviews
  pipeline-orchestrator ← meta-skill driving stages 1–6 end-to-end

Version Lifecycle

All artifacts follow a three-state lifecycle controlled by the PM:

  1. DRAFT — Artifacts are generated and freely iterated. Edits overwrite in place.
  2. FINALIZED — PM says "finalize this version". Artifacts archived to docs/pm-artifacts/archive/<artifact>-v<version>.md, CHANGELOG updated, version locked.
  3. NEW ITERATION — PM provides updated inputs. scope-analyzer runs delta analysis against the finalized baseline before any regeneration.

Installation

Via npm (recommended)

npx pm-ai-toolkit install

Or install the CLI globally:

npm install -g pm-ai-toolkit
pm-ai-toolkit install

This copies all plugin files (skills, agents, hooks) into ~/.cursor/plugins/local/pm-ai-toolkit/. Restart Cursor or Claude Code to activate.

CLI Commands

| Command | Description | |---------|-------------| | pm-ai-toolkit install | Install or update the plugin | | pm-ai-toolkit update | Alias for install | | pm-ai-toolkit uninstall | Remove the plugin | | pm-ai-toolkit status | Show installed version and check for updates | | pm-ai-toolkit doctor | Run diagnostics: Node version, Cursor dir, file integrity, skill/agent counts | | pm-ai-toolkit init | Create a pm-toolkit.config.yaml in the current project with commented defaults | | pm-ai-toolkit validate-config | Validate pm-toolkit.config.yaml — exits with code 1 if errors found | | pm-ai-toolkit project-status | Show all artifact files, versions, and statuses for the current project (--json for machine-readable output) | | pm-ai-toolkit help | Print usage information | | pm-ai-toolkit --version | Print version number |

Platform Support

| Platform | npm CLI | install.sh | |----------|---------|------------| | macOS | ✓ | ✓ | | Linux | ✓ | ✓ | | Windows (native) | ✓ | ✗ (use npm) | | Windows (WSL) | ✓ | ✓ |

Via script

git clone <repo-url> && cd pm-ai-toolkit && ./install.sh

Configuration

Copy the example config to your project root to customize behavior:

pm-ai-toolkit init

Key settings in pm-toolkit.config.yaml:

output_dir: docs/pm-artifacts/     # Where artifacts are saved
diagram_format: both                # dot | mermaid | both
excel_export: auto                  # auto | always | never
tech_stack: ""                      # Pre-set stack; skips auto-detection
project_name: ""                    # Used in artifact filenames
stakeholder_update_tone: ask        # exec | engineering | customer | ask
auto_approve_stages: []             # Skills that skip PM approval gate

The config file is validated by a JSON Schema (pm-toolkit.config.schema.json) — editors with YAML Language Server support will provide autocomplete and inline validation automatically.


Explicit Invocation

Skills activate automatically based on context. You can also invoke them directly:

Use pm-ai-toolkit:pipeline-orchestrator
Use pm-ai-toolkit:status-dashboard
Use pm-ai-toolkit:brainstorming
Use pm-ai-toolkit:knowledge-ingestion
Use pm-ai-toolkit:feature-extraction
Use pm-ai-toolkit:user-story-generation
Use pm-ai-toolkit:task-decomposition
Use pm-ai-toolkit:test-case-generation
Use pm-ai-toolkit:exit-criteria-generation
Use pm-ai-toolkit:architecture-diagrams
Use pm-ai-toolkit:scope-analyzer
Use pm-ai-toolkit:risk-register
Use pm-ai-toolkit:version-changelog
Use pm-ai-toolkit:sprint-planner
Use pm-ai-toolkit:stakeholder-update
Use pm-ai-toolkit:rollback

Directory Structure

pm-ai-toolkit/
  package.json
  pm-toolkit.config.example.yaml
  pm-toolkit.config.schema.json
  bin/
    cli.js
  .cursor-plugin/
    plugin.json
  .claude-plugin/
    plugin.json
    marketplace.json
  hooks/
    hooks.json
    hooks-cursor.json
    run-hook.cmd
    session-start
  skills/
    _shared/
      conventions.md
    pipeline-orchestrator/
      SKILL.md
    status-dashboard/
      SKILL.md
    brainstorming/
      SKILL.md
    knowledge-ingestion/
      SKILL.md
    feature-extraction/
      SKILL.md
    user-story-generation/
      SKILL.md
      story-templates.md
    task-decomposition/
      SKILL.md
    test-case-generation/
      SKILL.md
      test-patterns.md
      excel-export.md
    exit-criteria-generation/
      SKILL.md
      criteria-templates.md
    architecture-diagrams/
      SKILL.md
      diagram-patterns.dot
      diagram-templates.md
      mermaid-templates.md
    scope-analyzer/
      SKILL.md
    risk-register/
      SKILL.md
    version-changelog/
      SKILL.md
      changelog-format.md
    sprint-planner/
      SKILL.md
    stakeholder-update/
      SKILL.md
    rollback/
      SKILL.md
  agents/
    requirements-analyst.md
    solution-architect.md
    spec-reviewer.md
    story-reviewer.md
    task-estimator.md
  tests/
    cli.test.js
    skills.test.js
  README.md
  CHANGELOG.md
  HOOKS.md
  INSTALLATION.md
  GETTING-STARTED.md
  CONTRIBUTING.md
  ARTIFACT-SCHEMA.md
  PLUGIN-REVIEW.md

License

MIT