🚀 Tasleemat (تسليمات) — Enterprise Bilingual PMO Operating System & Python SDK
Tasleemat (تسليمات) is a production-grade, open-source Project Management Office (PMO) operating system and programmatic Python library designed for Project Managers, PMO Directors, Business Leaders, Data Engineers, and AI Agents.
It provides 114 standardized, bilingual (English & Arabic) project management deliverables (228 synchronized form bundles total) covering the complete project lifecycle—from strategic portfolio roadmaps and business cases to scope baselines, risk registers, stage-gate reviews, Earned Value Analysis (EVA), and project closeouts.
With Version 2.4.1, Tasleemat delivers a complete programmatic Python API, standard Model Context Protocol (MCP) server, standalone offline rendering, structural JSON schema data contracts with strict and draft validation modes, and machine-readable downstream integration contracts for AI agent orchestrators (such as Maharat).
🌟 What's New in v2.4.1
- ⚡ Native Model Context Protocol (MCP) Server: Plug Tasleemat directly into Claude Desktop, Cursor, and OpenCode via
tasleemat-mcporpython -m tasleemat.mcp. - 🧩 First-Class Programmatic Python API: Access all 114 artifact definitions, bundles, templates, guides, prompts, and schemas directly via
import tasleemat. - 🔍 Structural Data Validation Engine: Validate artifact data payloads against formal Draft 2020-12 companion JSON schemas with field-level error reporting (
validate_artifact_data). - 📝 Strict & Draft Validation Modes: Support production sign-offs with strict validation while enabling in-progress agent workflows with non-blocking draft warnings.
- 🎨 Standalone Document Rendering: Render artifacts to styled, print-ready HTML with zero external services and strict immutability protection for source templates (
render_artifact). - 🤖 Agent Orchestrator Integration (Maharat Ready): Machine-readable catalog, stable artifact IDs (
PMO-XX.YY), cryptographic SHA-256 content fingerprints, and standardized bilingual terminology getters (get_lexicon). - 🔒 Absolute Immutability & Traceability: Guaranteed immutability of the source
forms/catalog with runtime guards against unintended overwrites.
💻 Installation
Install the official package from PyPI:
pip install tasleemat
Verify your installation:
tasleemat --help
🚀 Python SDK Quickstart
1. Catalog Discovery & Metadata Retrieval
Discover registered PMO deliverables and inspect their phase, tailoring profile, and cryptographic fingerprints:
import tasleemat
# List all 114 registered artifacts
artifacts = tasleemat.list_artifacts()
print(f"Discovered {len(artifacts)} standardized deliverables.")
# Filter by project lifecycle phase
planning_artifacts = tasleemat.list_artifacts(phase="Planning")
# Retrieve detailed metadata for a specific deliverable
charter = tasleemat.get_artifact_definition("PMO-03.01")
print(charter["name_en"]) # "PROJECT CHARTER"
print(charter["name_ar"]) # "ميثاق المشروع"
print(charter["phase"]) # "Initiating"
print(charter["tier"]) # "Tier 3 (Lean)"
print(charter["fingerprint"]) # SHA-256 content fingerprint
2. Bilingual Asset Retrieval
Retrieve templates, guides, AI prompts, data schemas, and dictionaries without parsing directory structures:
from tasleemat import get_artifact_asset, get_artifact_assets
# Retrieve specific asset directly (by role and language)
# Roles: "template", "guide", "prompt", "schema", "dictionary", "example"
en_template = get_artifact_asset("PMO-03.01", role="template", lang="en")
ar_template = get_artifact_asset("PMO-03.01", role="template", lang="ar")
# Or fetch the entire asset bundle
bundle_ar = get_artifact_assets("PMO-03.01", lang="ar")
print(bundle_ar.get_guide_content())
schema_dict = bundle_ar.get_schema_data()
3. Structural Data Validation (strict vs draft)
Validate structured project data against formal companion schemas:
from tasleemat import validate_artifact_data
project_charter_data = {
"artifact_id": "PMO-03.01",
"project_name": "Digital Transformation Initiative",
"project_code": "PRJ-2026-001",
"project_manager": "Sarah Jenkins, PMP",
"sponsor": "Executive Committee",
"business_need": "Modernize legacy transaction platforms to reduce latency by 40%.",
"project_purpose": "Deploy enterprise microservices architecture.",
"objectives": [
{"objective": "Migrate 10 core services", "target_date": "2026-12-31"}
],
"high_level_requirements": ["99.99% SLA availability", "Zero data loss during cutover"],
"summary_budget": {"total_budget": 1500000.0, "currency": "SAR"}
}
# Strict Mode: For formal stage-gate approvals and final baselines
report = validate_artifact_data("PMO-03.01", project_charter_data, mode="strict")
if report.valid:
print("✅ Document structure is strictly valid for stage-gate submission!")
else:
for err in report.errors:
print(f"❌ Error at {err.field_path}: {err.message} (Code: {err.code})")
# Draft Mode: For intermediate agent loops or draft authoring (produces warnings, does not fail)
draft_report = validate_artifact_data("PMO-03.01", {"project_name": "Draft Project"}, mode="draft")
print(f"Draft valid: {draft_report.valid}, Warnings: {len(draft_report.warnings)}")
4. Standalone Offline Document Rendering
Render any artifact to publication-ready styled HTML:
from tasleemat import render_artifact
# Render Project Charter to a styled, print-ready HTML document
html_output = render_artifact("PMO-03.01", lang="ar", out_path="./output/charter_ar.html")
print("Rendered artifact saved to ./output/charter_ar.html")
5. Standardized Bilingual PMO Terminology
Access standardized PMI/DGA English-Arabic terminology mappings:
from tasleemat import get_lexicon
# Retrieve full bilingual PMO lexicon
lexicon = get_lexicon()
print(f"Loaded {len(lexicon)} terms.")
# Filter by lifecycle category
initiating_terms = get_lexicon(category="Initiating")
for item in initiating_terms[:3]:
print(f"{item['en_name']} <---> {item['ar_name']}")
🛠️ Global Command-Line Interface (CLI)
The tasleemat CLI provides workspace scaffolding, form searches, AI document auto-generation, and testing:
# 1. Complete CLI reference
tasleemat --help
# 2. Interactive project workspace scaffolder
tasleemat init
# 3. Fast-track automated scaffolding (Tier 2 Standard, Agile Pack, Arabic templates)
tasleemat init --tier 2 --pack agile --lang ar --name "منصة السحابة" --code "PRJ-2026-02" --out ./My_Project
# 4. Search deliverable forms by keyword
tasleemat search "Risk" --lang en
tasleemat search "ميثاق" --lang ar
# 5. List all 114 forms in catalog
tasleemat list --lang en
# 6. Auto-fill project deliverables using AI from meeting notes
tasleemat generate --form PMO-03.01 --notes ./meeting_notes.txt --out ./Project_Charter.md
# 7. Run automated test suite
tasleemat test -v
📦 5-File Synchronized Artifact Architecture
Every one of the 114 deliverables is organized as a synchronized bundle of 5 files:
| File Type | File Pattern | Purpose |
|---|---|---|
| Printable Template | *_Template.md / *_قالب.md |
Human-facing document structure with sign-off headers and Document Control tables |
| Practitioner Guide | *_Guide.md / *_دليل.md |
In-depth operational guide, field-by-field instructions, and dependency rules |
| LLM Generation Prompt | *.md |
Engineered system prompt for automated AI drafting and LLM completion |
| JSON Data Schema | *.json |
Machine-readable schema specification for API ingestion and validation |
| Tabular Dictionary | *.csv |
4-column structured dictionary for spreadsheet, PowerBI, and database ingestion |
🗺️ Project Lifecycle Overview (114 Deliverables)
| Phase Code | Phase Name | Deliverables Count | Focus Area |
|---|---|---|---|
| 00 | Program & Portfolio Management | 6 Forms | Portfolio roadmaps, OKR alignment, capacity planning, PMO maturity |
| 01 | Business & Value Delivery | 4 Forms | Business cases, benefits realization plans, value registers |
| 02 | Project Approach & Tailoring | 6 Forms | Tailoring strategy, AI governance, AI ethics baselines, model cards |
| 03 | Initiating | 5 Forms | Project charter, product vision, assumption log, stakeholder register |
| 04 | Planning | 52 Forms | 12 Domains: Scope, Schedule, Cost, Quality, Resources, Communications, Risk, Procurement, Stakeholder, OCM, Sustainability/ESG |
| 05 | Executing | 12 Forms | Issue log, change requests, retrospectives, team performance |
| 06 | Monitoring & Controlling | 12 Forms | Status reports, Earned Value Analysis (EVA), UAT signoff, flow metrics |
| 07 | Closing | 5 Forms | Lessons learned, contract closeouts, operational handover, archive |
🤖 Using Tasleemat & OKF with LLMs (Claude, ChatGPT, OpenCode & Coding Agents)
Tasleemat is natively engineered for Generative AI workflows, Large Language Models (LLMs), and AI coding assistants (Claude, ChatGPT, OpenCode, Cursor, GitHub Copilot):
- In Standard Chat LLMs (Claude & ChatGPT):
- Copy any engineered LLM prompt from
forms/en/orforms/ar/(e.g.03_01_Project_Charter.md) and append raw kickoff/meeting notes. The LLM generates a complete, PMI-aligned deliverable with Document Control headers. - Upload
forms/templates anddocs/LEXICON.jsoninto Custom GPTs or Claude Projects as persistent institutional knowledge.
- Copy any engineered LLM prompt from
- In Agentic IDEs (OpenCode, Cursor, Copilot):
- Use
@context referencing (e.g.@03_01_Project_Charter_Template.md Fill this project charter for...) to have AI coding agents generate conforming deliverables directly into your workspace.
- Use
- Structured Tool Use & Function Calling via OKF:
- The root
datapackage.jsonconforms to the Open Knowledge Foundation (OKF) standard. Pass companion JSON schemas into OpenAI Tools or Claude Tool Use parameters to guarantee structured JSON outputs without hallucinated fields.
- The root
- Self-Correction Feedback Loops:
- Run
validate_artifact_dataon LLM-generated JSON payloads. If errors occur, pass exact JSON pointer error paths back to the model to self-correct automatically.
- Run
🤖 Integration Architecture for Downstream Agents (e.g. Maharat)
Tasleemat v2.4.0 establishes a clean, decoupled boundary for downstream AI agents and workflow orchestration platforms:
┌────────────────────────────────────────────────────────┐
│ DOWNSTREAM AGENTS / MAHARAT │
│ - Methodological workflows & PMBOK skill guidance │
│ - Input suitability, evidence & business checks │
│ - Stage-gate approvals & multi-agent decisions │
└───────────────────────────┬────────────────────────────┘
│ imports & queries
▼
┌────────────────────────────────────────────────────────┐
│ TASLEEMAT OPERATING SYSTEM │
│ - 114 Canonical Artifacts & Stable IDs (PMO-XX.YY) │
│ - Bilingual Templates, Guides & Terminology (Lexicon) │
│ - Structural Data Contracts & JSON Schema Validation │
│ - Standalone Offline Rendering & Template Preservation│
└────────────────────────────────────────────────────────┘
- Tasleemat owns: Canonical artifact definitions, stable IDs, templates, structural data schemas, format validation (
strictanddraft), bilingual terminology, and offline rendering. - Agent Orchestrators (Maharat) own: Methodological skills, business suitability checks, evidence validation, cross-artifact consistency, and human approval workflows.
📜 Standards Alignment
- PMI PMBOK® Guide: 6th, 7th & 8th Edition alignment.
- ISO Standards: ISO 21500:2021 (Project Governance) & ISO 21502:2020 (Project Management).
- AI Governance: NIST AI Risk Management Framework (AI RMF 1.0) & EU AI Act readiness.
- Open Data: Open Knowledge Foundation (OKF) Frictionless Data Package specification.
- Saudi DGA PMO Standards: Terminology aligned with official government digital governance frameworks.
🔗 Links & Resources
- GitHub Repository: github.com/fakhruldeen/Tasleemat
- Interactive Web Portal: fakhr.me/Tasleemat
- Documentation: docs/README.md
- Zenodo DOI: 10.5281/zenodo.23193523
Metadata
Release files for tasleemat 2.4.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| tasleemat-2.4.1.tar.gz | 5.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tasleemat-2.4.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.1 MB
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