Agent skill

Unified Deliverables Flow

by HKUDS in HKUDS/OpenSpace

Generate spreadsheets, diagrams, and PDF reports in a phased workflow with explicit iteration budgets and error recovery

MITAuto-check passedDocuments & Office

Install Unified Deliverables Flow

skills CLI
$ npx skills add HKUDS/OpenSpace --skill unified-deliverables-flow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HKUDS/OpenSpace unified-deliverables-flow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/benchmarks/gdpval/skills/pdf-checklist-workflow-enhanced .claude/skills/unified-deliverables-flow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
unified-deliverables-flow
GitHub stars
7.8k
Token cost
~3.8k tokens
SKILL.md length
742 words
Files
2
Skills in repo
199
Repo updated
First seen
Licence
MIT

At a glance

Generate spreadsheets, diagrams, and PDF reports in a phased workflow with explicit iteration budgets and error recovery

  • Works in 4 steps: Pre-Work Setup (1 iteration max) → Spreadsheet Generation (Budget: 8… → Diagram Generation (Budget: 8 iterations) → …
  • Tasks that involve Excel spreadsheets
  • SKILL.md covers Overview, Critical: Iteration Budget…, Step-by-Step Instructions and Error Recovery & Fallback…, plus 5 more sections
  • Calls python3 and pip

What it does

Unified Deliverables Flow is an agent skill from HKUDS/OpenSpace. Generate spreadsheets, diagrams, and PDF reports in a phased workflow with explicit iteration budgets and error recovery

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in Documents & Office, covering Excel spreadsheets, PDF and Diagrams. The repository describes itself as: "OpenSpace: The Skill Management Layer for AI Agents" -- https://open-space.cloud/. The licence is MIT.

When your agent uses it

  • Tasks that involve Excel spreadsheets
  • Tasks that involve PDF
  • Tasks that involve Diagrams

Example prompts

  • “/unified-deliverables-flow”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Pre-Work Setup (1 iteration max)
  2. Spreadsheet Generation (Budget: 8 iterations)
  3. Diagram Generation (Budget: 8 iterations)
  4. PDF Report Generation (Budget: 8 iterations)

What it can do on your machine

Read from SKILL.md and the folder at commit 3827781. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Unified Deliverables Flow loads about 3.8k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 742 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HKUDS/OpenSpace at commit 3827781, republished under its MIT licence (© HKUDS). 742 words, ~3,814 tokens.

Download SKILL.mdSave it as .claude/skills/unified-deliverables-flow/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
unified-deliverables-flow
description
Generate spreadsheets, diagrams, and PDF reports in a phased workflow with explicit iteration budgets and error recovery

Unified Multi-Deliverable Generation Workflow

This skill provides a structured, phased approach for creating multiple deliverable types (spreadsheets, diagrams, PDF reports) in a single cohesive workflow with explicit iteration budgeting to prevent premature exhaustion.

Overview

Use this workflow when you need to:

  • Generate multiple deliverable types (Excel, images, PDFs) in one task
  • Ensure balanced iteration allocation across all deliverables
  • Handle tool failures gracefully with retries and fallbacks
  • Produce downloadable artifacts with verified paths

Critical: Iteration Budget Allocation

Allocate iterations BEFORE starting work:

PhaseDeliverableBudgetCheckpoint
Phase 1Spreadsheet8 iterationsFile exists + readable
Phase 2Diagram8 iterationsFile exists + >1KB
Phase 3PDF Report8 iterationsFile exists + ARTIFACT_PATH output
BufferError recovery6 iterationsRemaining for retries
TotalAll deliverables30 iterationsAll verified

Rules:

  • Complete each phase before moving to the next
  • If a phase exceeds budget, use fallback strategy (see below)
  • Never spend >10 iterations on a single deliverable without checkpoint
  • Verify each deliverable before proceeding

Step-by-Step Instructions

Phase 0: Pre-Work Setup (1 iteration max)
  1. Define all deliverables explicitly:

    Deliverable 1: hardware_selection_table.xlsx (Excel with comparison data)
    Deliverable 2: cnc_workcell_layout.png (PNG diagram of layout)
    Deliverable 3: final_report.pdf (PDF summary report)
  2. Verify workspace is accessible:

    run_shell
      command: ls -la /workspace/ && mkdir -p /workspace/artifacts
  3. Set path variables for consistency:

    • All files go to /workspace/ or /workspace/artifacts/
    • Use absolute paths in all code
    • Never use relative paths like ./output.xlsx
Phase 1: Spreadsheet Generation (Budget: 8 iterations)

Step 1.1: Choose approach

MethodToolBest For
Direct Pythonexecute_code_sandboxQuick generation, simple tables
Shell agentshell_agentComplex logic, error recovery

Step 1.2: Create spreadsheet code

python
from openpyxl import Workbook
from openpyxl.styles import Font, Alignment, Border, Side

def create_hardware_table():
    wb = Workbook()
    ws = wb.active
    ws.title = "Hardware Selection"
    
    # Headers with styling
    headers = ["Component", "Option A", "Option B", "Option C", "Recommendation"]
    for col, header in enumerate(headers, 1):
        cell = ws.cell(row=1, column=col, value=header)
        cell.font = Font(bold=True)
        cell.alignment = Alignment(horizontal='center')
    
    # Data rows
    data = [
        ["Controller", "PLC-X100 ($500)", "PLC-Y200 ($650)", "PLC-Z300 ($800)", "PLC-Y200"],
        ["Motor", "Servo-500W ($300)", "Servo-750W ($400)", "Stepper-1kW ($250)", "Servo-750W"],
        ["Sensor", "Proximity-S1 ($50)", "Vision-V2 ($200)", "Laser-L3 ($150)", "Vision-V2"]
    ]
    
    for row_idx, row_data in enumerate(data, 2):
        for col_idx, value in enumerate(row_data, 1):
            ws.cell(row=row_idx, column=col_idx, value=value)
    
    # Auto-adjust column widths
    for col in ws.columns:
        max_length = max(len(str(cell.value)) for cell in col if cell.value)
        ws.column_dimensions[col[0].column_letter].width = min(max_length + 2, 25)
    
    output_path = '/workspace/hardware_selection_table.xlsx'
    wb.save(output_path)
    print(f'SUCCESS: Spreadsheet created at {output_path}')
    print(f'ARTIFACT_PATH:{output_path}')
    return output_path

create_hardware_table()

Step 1.3: Execute with verification

execute_code_sandbox
  code: <spreadsheet code from Step 1.2>
  language: python

Step 1.4: Verify (REQUIRED before proceeding)

run_shell
  command: ls -lh /workspace/*.xlsx && python3 -c "import openpyxl; openpyxl.load_workbook('/workspace/hardware_selection_table.xlsx')"

Checkpoint criteria:

  • ✓ File exists
  • ✓ Size > 1KB
  • ✓ No errors opening file
  • ✗ If failed, retry once with shell_agent, then proceed to Phase 2 with note
Phase 2: Diagram Generation (Budget: 8 iterations)

Step 2.1: Choose diagram type and tool

Diagram TypeToolLibrary
Flowchart/Blocksexecute_code_sandboxmatplotlib, graphviz
Layout/Floorplanshell_agentmatplotlib, PIL
Architectureexecute_code_sandboxmatplotlib, diagram

Step 2.2: Create diagram code (matplotlib example)

python
import matplotlib.pyplot as plt
import matplotlib.patches as patches

def create_layout_diagram():
    fig, ax = plt.subplots(figsize=(12, 8))
    ax.set_xlim(0, 100)
    ax.set_ylim(0, 80)
    ax.set_aspect('equal')
    ax.set_title('CNC Workcell Layout', fontsize=16, pad=20)
    
    # Define workcell components
    components = [
        {'label': 'CNC Machine', 'xy': (30, 40), 'w': 25, 'h': 20, 'color': '#3498db'},
        {'label': 'Robot Arm', 'xy': (60, 40), 'w': 15, 'h': 15, 'color': '#e74c3c'},
        {'label': 'Material Rack', 'xy': (10, 20), 'w': 15, 'h': 40, 'color': '#2ecc71'},
        {'label': 'Control Panel', 'xy': (75, 60), 'w': 12, 'h': 10, 'color': '#f39c12'},
        {'label': 'Safety Zone', 'xy': (25, 35), 'w': 50, 'h': 30, 'color': 'none', 'edge': '#95a5a6', 'dashed': True}
    ]
    
    for comp in components:
        if comp.get('edge'):
            rect = patches.Rectangle(
                (comp['xy'][0], comp['xy'][1]), 
                comp['w'], comp['h'],
                linewidth=2, 
                edgecolor=comp['edge'],
                facecolor=comp['color'],
                linestyle='--' if comp.get('dashed') else '-'
            )
        else:
            rect = patches.Rectangle(
                (comp['xy'][0], comp['xy'][1]), 
                comp['w'], comp['h'],
                linewidth=2, 
                edgecolor='black',
                facecolor=comp['color']
            )
        ax.add_patch(rect)
        ax.text(
            comp['xy'][0] + comp['w']/2, 
            comp['xy'][1] + comp['h']/2, 
            comp['label'],
            ha='center', va='center', fontsize=10, fontweight='bold'
        )
    
    plt.grid(True, alpha=0.3)
    plt.xlabel('Distance (m)')
    plt.ylabel('Distance (m)')
    
    output_path = '/workspace/cnc_workcell_layout.png'
    plt.savefig(output_path, dpi=150, bbox_inches='tight')
    plt.close()
    print(f'SUCCESS: Diagram created at {output_path}')
    print(f'ARTIFACT_PATH:{output_path}')
    return output_path

create_layout_diagram()

Step 2.3: Execute and verify

execute_code_sandbox
  code: <diagram code from Step 2.2>
  language: python

Verification:

run_shell
  command: ls -lh /workspace/*.png && file /workspace/*.png

Checkpoint criteria:

  • ✓ File exists
  • ✓ Size > 1KB
  • ✓ File type confirmed as PNG/image
  • ✗ If failed after 2 retries, use shell_agent fallback, then proceed
Phase 3: PDF Report Generation (Budget: 8 iterations)

Step 3.1: Prepare content aggregation

Gather data from previous phases:

  • Spreadsheet: key findings, recommendations
  • Diagram: visual summary
  • Additional: scoring, conclusions

Step 3.2: Create PDF generation code

python
from reportlab.lib import colors
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, Image
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import inch
from reportlab.lib.enums import TA_CENTER, TA_LEFT

def create_final_report(output_path):
    doc = SimpleDocTemplate(output_path, pagesize=letter,
                           rightMargin=0.75*inch, leftMargin=0.75*inch,
                           topMargin=0.75*inch, bottomMargin=0.75*inch)
    styles = getSampleStyleSheet()
    story = []
    
    # Custom styles
    title_style = ParagraphStyle('CustomTitle', parent=styles['Heading1'],
                                  fontSize=20, spaceAfter=30, alignment=TA_CENTER,
                                  fontName='Helvetica-Bold')
    heading_style = ParagraphStyle('CustomHeading', parent=styles['Heading2'],
                                    fontSize=14, spaceAfter=12, spaceBefore=20,
                                    fontName='Helvetica-Bold')
    
    # Title
    story.append(Paragraph("CNC Workcell Implementation Report", title_style))
    story.append(Spacer(1, 0.5*inch))
    
    # Executive Summary
    story.append(Paragraph("Executive Summary", heading_style))
    summary_text = """
    This report presents the hardware selection analysis and workcell layout 
    for the proposed CNC implementation. After evaluating multiple options across 
    controllers, motors, and sensors, recommended configurations balance cost, 
    performance, and reliability.
    """
    story.append(Paragraph(summary_text, styles['Normal']))
    story.append(Spacer(1, 0.3*inch))
    
    # Hardware Selection Table
    story.append(Paragraph("Hardware Selection Summary", heading_style))
    data = [
        ['Component', 'Recommended Option', 'Cost', 'Rationale'],
        ['Controller', 'PLC-Y200', '$650', 'Best cost/performance balance'],
        ['Motor', 'Servo-750W', '$400', 'Adequate power with precision'],
        ['Sensor', 'Vision-V2', '$200', 'Enables quality inspection']
    ]
    
    table = Table(data, colWidths=[1.5*inch, 1.7*inch, 1*inch, 2.3*inch])
    table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (-1, 0), colors '#2c3e50'),
        ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
        ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
        ('FONTSIZE', (0, 0), (-1, 0), 11),
        ('BOTTOMPADDING', (0, 0), (-1, 0), 12),
        ('BACKGROUND', (0, 1), (-1, -1), colors.beige),
        ('GRID', (0, 0), (-1, -1), 1, colors.black),
        ('VALIGN', (0, 0), (-1, -1), 'MIDDLE')
    ]))
    story.append(table)
    story.append(Spacer(1, 0.4*inch))
    
    # Layout Diagram Reference
    story.append(Paragraph("Workcell Layout", heading_style))
    story.append(Paragraph("See attached diagram: cnc_workcell_layout.png", styles['Normal']))
    story.append(Spacer(1, 0.2*inch))
    
    # Recommendations
    story.append(Paragraph("Implementation Recommendations", heading_style))
    rec_text = """
    1. Begin with controller installation and configuration
    2. Integrate motor drives and verify motion control
    3. Install and calibrate vision system
    4. Conduct safety zone validation
    5. Perform full system integration testing
    """
    story.append(Paragraph(rec_text, styles['Normal']))
    story.append(Spacer(1, 0.5*inch))
    
    # Footer
    story.append(Spacer(1, 0.5*inch))
    footer_style = ParagraphStyle('Footer', parent=styles['Normal'],
                                   fontSize=9, alignment=TA_CENTER, textColor=colors.grey)
    story.append(Paragraph("Generated by Unified Deliverables Workflow", footer_style))
    
    doc.build(story)
    print(f'SUCCESS: PDF report created at {output_path}')
    print(f'ARTIFACT_PATH:{output_path}')
    return output_path

create_final_report('/workspace/final_report.pdf')

Step 3.3: Execute with explicit artifact path

execute_code_sandbox
  code: <PDF code from Step 3.2>
  language: python

Step 3.4: Final verification

run_shell
  command: ls -lh /workspace/*.pdf && echo "---" && ls -lh /workspace/*.xlsx /workspace/*.png

Checkpoint criteria:

  • ✓ PDF file exists
  • ✓ Size > 10KB (reports should be substantial)
  • ✓ ARTIFACT_PATH was output
  • ✓ All three deliverables verified

Error Recovery & Fallback Strategies

When execute_code_sandbox fails repeatedly:

Strategy 1: Use shell_agent (more resilient)

shell_agent
  task: Create an Excel file at /workspace/hardware_selection_table.xlsx with hardware comparison data including controllers, motors, and sensors with costs and recommendations

Strategy 2: Simplify the code

  • Remove complex styling
  • Use basic libraries only (csv instead of openpyxl if needed)
  • Reduce dependencies

Strategy 3: Change output format

  • Excel → CSV if openpyxl fails
  • PNG → SVG if PIL/matplotlib fails
  • PDF → Markdown + convert later
Show full SKILL.md (290 more words)Show less
When iteration budget is running low:
Iterations RemainingAction
< 10Skip non-critical formatting, use minimal viable output
< 5Use simplest possible implementation, skip verification
< 3Output text summary with file paths, request manual generation

Best Practices

  1. Phase sequentially - Complete and verify each phase before moving on
  2. Use absolute paths - Always /workspace/filename.ext, never relative
  3. Output ARTIFACT_PATH - Every successful generation must print this
  4. Verify before proceeding - Run shell check after each deliverable
  5. Track iteration count - Count tool calls, stop at 25 to leave buffer
  6. Simplify on failure - If complex code fails, strip to minimum viable
  7. Document decisions - Note why fallback was used for future reference

Quick Reference: Tool Selection

TaskPrimary ToolFallback Tool
Spreadsheetexecute_code_sandbox (openpyxl)shell_agent (pandas)
Diagramexecute_code_sandbox (matplotlib)shell_agent (graphviz)
PDF Reportexecute_code_sandbox (reportlab)shell_agent (fpdf)
Verificationrun_shell (ls, file)read_file (for content check)

Complete Workflow Checklist

  • Phase 0: Defined all 3 deliverables with paths
  • Phase 0: Verified workspace accessibility
  • Phase 1: Spreadsheet created and verified (< 8 iterations)
  • Phase 2: Diagram created and verified (< 8 iterations)
  • Phase 3: PDF created and verified (< 8 iterations)
  • All ARTIFACT_PATH outputs captured
  • Final verification: all files exist with appropriate sizes
  • Total iterations used ≤ 30

Troubleshooting

ProblemImmediate Action
execute_code_sandbox returns "[ERROR] unknown error"Retry once, then switch to shell_agent
File not found after executionCheck actual path with run_shell: ls /workspace/
ARTIFACT_PATH not outputRe-run with explicit print statement
Iteration budget nearly exhaustedSkip remaining deliverables, document what was created
Library import failsAdd !pip install <library> at code start
  • execute_code_sandbox - Primary tool for code execution (Python)
  • shell_agent - Fallback for complex tasks or when sandbox fails
  • run_shell - Verification and workspace inspection
  • read_file - Content verification (type: xlsx, png, pdf)
  • create_file - Alternative for text-based outputs

© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in benchmarks/gdpval/skills/pdf-checklist-workflow-enhanced of HKUDS/OpenSpace.

  • SKILL.md
  • .skill_id

Open the folder on GitHubat commit 3827781

Compare with similar skills

Unified Deliverables Flow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Unified Deliverables Flow compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Unified Deliverables Flow this skillHKUDS/OpenSpace7.8k—~3.8kAutomated safety check: PassMIT
Report WritingGAIK-project/gaik-toolkit100—~4.9kAutomated safety check: PassMIT
Document ConverterBlackBeltTechnology/pi-agent-dashboard315—~999Automated safety check: PassMIT
MarkitdownImCa0/just-laws78114 repos~3.2kAutomated safety check: NotesMIT
Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences2742 repos~2.7kAutomated safety check: PassApache-2.0
PDFzai-org/ZCode7.7k—~18kAutomated safety check: NotesProprietary

Similar skills

  • Report Writing

    GAIK-project/gaik-toolkit

    Converts scattered documents and media (recordings, notes, diagrams, PDFs, spreadsheets) into structured MS Word reports.

    100 GitHub stars~4.9k tokensUpdated 2 days ago
    Documents & OfficeAuto-check passed
  • Document Converter

    BlackBeltTechnology/pi-agent-dashboard

    Convert documents bidirectionally via the pi-doc-engine facade: ingest PDF/DOCX/PPTX/XLSX to provenance-stamped Markdown (with OCR), and produce templated DOCX/PDF from Markdown with diagrams, TOC…

    315 GitHub stars~999 tokensUpdated yesterday
    Documents & OfficeAuto-check passed
  • Markitdown

    ImCa0/just-laws

    Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.

    781 GitHub starsUsed in 14 repos~3.2k tokens
    Documents & OfficeAuto-check: notes
  • Instrument Data To Allotrope

    aws-samples/amazon-bedrock-agents-healthcare-lifesciences

    Official

    Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.

    274 GitHub starsUsed in 2 repos~2.7k tokens
    Documents & OfficeAuto-check passed
  • PDF

    zai-org/ZCode

    Professional PDF toolkit covering four production workflows: reports, creative visuals, academic LaTeX, and existing PDF processing.

    7.7k GitHub stars~18k tokensUpdated yesterday
    Documents & OfficeAuto-check: notes
  • Jev SEO

    AgriciDaniel/jev-seo

    Full live SEO audit of any website from its homepage URL, powered by Jev (TypeSafe's System One model).

    543 GitHub stars~2.5k tokensUpdated 19 days ago
    Documents & OfficeAuto-check: notes

More from HKUDS/OpenSpace

All 199 skills in this repo
  • Walks through producing a master audio track plus stems in Python, from checking a reference file and timing sections by BPM to effects, a zip archive and final verification.

    7.8k GitHub stars~2.9k tokensUpdated 1 mo ago
    Auto-check passed
  • Handle cascading data retrieval tool failures by falling back to embedded knowledge generation

    7.8k GitHub stars~765 tokensUpdated 1 mo ago
    Auto-check passed
  • Gives an agent a workaround when its code-execution sandbox keeps failing: save the Python script to a file and run it through the shell instead.

    7.8k GitHub stars~588 tokensUpdated 1 mo ago
    Auto-check passed
  • A recovery routine for agents whose sandboxed code runner keeps failing: save the Python script to disk, then run it through the shell and read the output.

    7.8k GitHub stars~652 tokensUpdated 1 mo ago
    Auto-check passed
  • Fallback ladder for failed sandboxed code runs, plus the habit of fixing the working directory first so generated files land in the right place.

    7.8k GitHub stars~1.1k tokensUpdated 1 mo ago
    Auto-check passed
  • Fallback workflow for executing Python code when executecodesandbox fails repeatedly

    7.8k GitHub stars~1.1k tokensUpdated 1 mo ago
    Auto-check passed

Questions about Unified Deliverables Flow

What does Unified Deliverables Flow do?

Generate spreadsheets, diagrams, and PDF reports in a phased workflow with explicit iteration budgets and error recovery. Unified Deliverables Flow is an agent skill from HKUDS/OpenSpace.

When should I use Unified Deliverables Flow?

Unified Deliverables Flow fits situations like: tasks that involve Excel spreadsheets; tasks that involve PDF; tasks that involve Diagrams.

How do I install Unified Deliverables Flow in Claude Code?

Run `npx skills add HKUDS/OpenSpace --skill unified-deliverables-flow -a claude-code`. Or copy the skill folder (benchmarks/gdpval/skills/pdf-checklist-workflow-enhanced in HKUDS/OpenSpace) into .claude/skills/unified-deliverables-flow in your project. Claude Code loads it when a task matches its description.

How do I install Unified Deliverables Flow in Codex?

Run `npx skills add HKUDS/OpenSpace --skill unified-deliverables-flow -a codex`. Or copy the skill folder (benchmarks/gdpval/skills/pdf-checklist-workflow-enhanced in HKUDS/OpenSpace) into .agents/skills/unified-deliverables-flow in your project. Codex loads it when a task matches its description.

Can I use Unified Deliverables Flow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/OpenSpace --skill unified-deliverables-flow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/unified-deliverables-flow, .gemini/skills/unified-deliverables-flow, .github/skills/unified-deliverables-flow and .opencode/skills/unified-deliverables-flow in your project.

What does Unified Deliverables Flow need to run?

Going by SKILL.md and its folder, Unified Deliverables Flow needs the command-line tools its instructions call (python3 and pip). Our summary lists: Python 3.

Does Unified Deliverables Flow access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Unified Deliverables Flow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Unified Deliverables Flow use?

Unified Deliverables Flow is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Unified Deliverables Flow use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Unified Deliverables Flow?

Skills that share tags, products or a category with Unified Deliverables Flow: Report Writing (GAIK-project/gaik-toolkit, 100 stars), Document Converter (BlackBeltTechnology/pi-agent-dashboard, 315 stars), Markitdown (ImCa0/just-laws, 781 stars) and Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Unified Deliverables Flow?

HKUDS (a GitHub organization) maintains it in HKUDS/OpenSpace, which has 7,754 GitHub stars. The repository holds 199 skills in this directory. The repository was last updated on August 12, 2026.

Source: HKUDS/OpenSpace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.