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Projitive

Projitive is an abstract governance model and toolset for Agent-driven project execution, not a domain-specific task system.

Install / Use

/learn @yinxulai/Projitive
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Projitive

CI MCP Release Publish MCP npm version npm downloads

Language: English | 简体中文

Projitive is a governance model and MCP toolchain for Agent-driven delivery.

It helps teams turn "AI can code" into "AI can continuously deliver with traceability".

Version

  • Current spec: projitive-spec v1.0.0
  • MCP package: @projitive/mcp (2.x line)

60-Second Start

If you only read one section, read this:

  1. Start MCP: npx -y @projitive/mcp
  2. Configure scan roots and depth in your MCP client
  3. Run the loop: taskNext -> taskContext -> taskUpdate -> taskContext -> taskNext

Why teams use it:

  • Faster next-task selection
  • Clearer evidence traceability
  • More stable multi-agent delivery loops

5-Minute Demo (Copy/Paste)

Use this quick flow to experience the full loop: auto task discovery -> execution gate -> state write-back.

  1. Start MCP server
npx -y @projitive/mcp
  1. Connect Projitive MCP in your agent client
{
  "mcpServers": {
    "projitive": {
      "command": "npx",
      "args": ["-y", "@projitive/mcp"]
    }
  }
}
  1. Run this minimal loop
taskNext
taskContext
taskUpdate
taskContext
taskNext
  1. If no actionable task exists
taskCreate
taskNext

Expected result: the system does not stall on "no tasks" and helps the agent create and continue actionable work.

Why Use Projitive

Projitive turns agent execution from "can code" into "can continuously deliver." If you want an open-source governance loop that is practical, traceable, and sustainable in real projects, this is what it is built for.

  • Your agent always gets a next best action, even when backlog quality is poor.
  • Task state, roadmap state, and evidence stay aligned by design.
  • Documentation is maintained during execution, not deferred to release week.
  • New contributors can enter mid-cycle without breaking delivery rhythm.

Typical Open-Source Usage Scenarios

"Agent has nothing to do"

Instead of stalling, Projitive first checks latest branch/code changes to infer what the user recently worked on; if those changes are not synced into task/roadmap/report records, it performs governance synchronization first, then returns a discovery path and seed direction so the agent can create new actionable slices and keep moving.

"Project setup is incomplete"

Projitive bootstraps governance baseline (store, views, doc tracks) and repairs missing artifacts in partially initialized projects.

"Docs and execution drift apart"

Projitive enforces execution gates and context checks, so research, architecture decisions, and evidence links are updated as part of the same loop.

"Too many projects, no priority"

Projitive ranks opportunities by actionable intensity and recency, so agents focus where delivery impact is highest first.

How It Lands In Practice

Default Delivery Loop

flowchart LR
  A[taskNext / projectNext] --> B[taskContext / projectContext]
  B --> C[Update task and roadmap + docs]
  C --> D[taskContext verify]
  D --> E{More actionable work?}
  E -->|Yes| A
  E -->|No| F[Done / wait for new tasks]

Recommended minimal sequence:

  1. taskNext
  2. taskContext
  3. taskCreate/taskUpdate and/or roadmapCreate/roadmapUpdate
  4. taskContext
  5. taskNext

Governance Status Model

| Status | Meaning | Valid transitions | |---|---|---| | TODO | Ready to start | -> IN_PROGRESS, BLOCKED | | IN_PROGRESS | Actively executing | -> BLOCKED, DONE | | BLOCKED | Cannot proceed | -> TODO, IN_PROGRESS | | DONE | Completed with evidence | (terminal) |

BLOCKED tasks use structured blocker metadata (type, description, optional blockingEntity / unblockCondition / escalationPath) so unblocking can be automated.

Install and Configure

Use the published MCP package directly:

npx -y @projitive/mcp

MCP client config example:

{
  "mcpServers": {
    "projitive": {
      "command": "npx",
      "args": ["-y", "@projitive/mcp"],
      "env": {
        "PROJITIVE_SCAN_ROOT_PATHS": "/workspace/a:/workspace/b",
        "PROJITIVE_SCAN_MAX_DEPTH": "3"
      }
    }
  }
}

Environment variables (all optional):

| Variable | Default | Description | |---|---|---| | PROJITIVE_SCAN_ROOT_PATHS | ~ (home dir) | Discovery roots, platform path delimiter separated | | PROJITIVE_SCAN_ROOT_PATH | — | Legacy single-root fallback if above is unset | | PROJITIVE_SCAN_MAX_DEPTH | 3 | Discovery depth, integer 0–8 |

Deep-Dive Docs

For complete parameters and concrete call examples:

  • packages/mcp/README.md
  • packages/mcp/README_CN.md

Repo Map

  • designs/: spec and conventions
  • packages/mcp/: MCP server implementation
  • packages/skills/: skill package and helpers

Read Next

  • User-facing MCP guide: packages/mcp/README.md
  • Chinese MCP guide: packages/mcp/README_CN.md
  • Spec overview: designs/README.md
  • Chinese spec docs: designs/README_CN.md

Language Policy

  • English is default
  • Chinese documents use _CN suffix
View on GitHub
GitHub Stars83
CategoryProduct
Updated8d ago
Forks0

Languages

TypeScript

Security Score

80/100

Audited on Mar 30, 2026

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