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Deliverable Completion

OrganizationPopular
HKUDS
deliverable-completion

Clarifies that file creation tasks are complete when the deliverable is successfully written—no submission step required

Overview

PublisherHKUDS
RepositoryOpenSpace
Skill namedeliverable-completion
Stars
7.7K
Forks
918
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by HKUDS on GitHub. Read the source before you install it.

Installation

Install the Deliverable Completion AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HKUDS/OpenSpace.git /tmp/OpenSpace
mkdir -p .claude/skills
cp -r /tmp/OpenSpace/benchmarks/gdpval/skills/deliverable-completion .claude/skills/deliverable-completion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deliverable Completion in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deliverable Completion on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deliverable Completion is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Deliverable Completion Protocol

Purpose

This skill addresses a common misconception during document and file creation tasks: agents sometimes search for or attempt to use a submit_work, finalize, or similar tool after creating the deliverable. No such step is required. Task completion is achieved when the file is successfully created with the required content.

Core Principle

File creation = Task completion

When a task requests you to create a document, report, script, or any file-based deliverable, the task is complete once:

  1. The file has been written to disk
  2. The file contains the required content
  3. The file is in the correct format and location

There is no additional submission, finalization, or confirmation step needed.

Execution Workflow

Step 1: Create the Deliverable

Use the appropriate file creation method for your task:

python
# For programmatic file creation
with open('deliverable.docx', 'wb') as f:
    f.write(document_content)
bash
# For shell-based creation
echo "content" > output.txt

Or use available tools like write_file, create_file, etc.

Step 2: Verify Creation

Confirm the file exists and contains expected content:

bash
ls -la deliverable.docx
# or
cat output.txt

Step 3: Declare Completion

Once verification passes, the task is complete. Do not:

  • Search for a submit_work tool
  • Look for a finalize_task function
  • Attempt to "upload" or "submit" the file elsewhere
  • Add extra confirmation steps

Simply report that the deliverable has been created successfully.

Common Mistakes to Avoid

❌ Incorrect✅ Correct
Creating file, then searching for submit toolCreating file, verifying, declaring done
Assuming a finalization API existsTreating file creation as the final step
Adding unnecessary confirmation stepsCompleting after successful write

Example Task Flow

Task: "Create a negotiation strategy document covering BATNA, ZOPA, and timeline."

Correct Execution:

  1. Write the document content
  2. Save as negotiation_strategy.docx
  3. Verify file exists (~43KB, contains all sections)
  4. Report: "Negotiation strategy document created successfully"
  5. Task complete — no further action needed

When This Applies

  • Document creation (.docx, .pdf, .md, .txt)
  • Code file generation (.py, .sh, .js)
  • Data exports (.csv, .json, .xlsx)
  • Configuration files (.yaml, .toml, .ini)
  • Any file-based deliverable

When This Does NOT Apply

  • Tasks explicitly requiring external submission (e.g., "submit to API endpoint")
  • Tasks requiring human review/approval workflows
  • Tasks where the file is an intermediate step (not the final deliverable)

Frequently asked questions

What does the Deliverable Completion AI skill do?

Clarifies that file creation tasks are complete when the deliverable is successfully written—no submission step required

Why use Deliverable Completion on TypingMind?

Because you install it once and use it with any model. Deliverable Completion is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deliverable Completion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/deliverable-completion. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deliverable Completion?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deliverable Completion?

As many as you like. As long as a model supports skills, you can use Deliverable Completion with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deliverable Completion AI skill free?

Yes. It is published on GitHub by HKUDS under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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