Sdd Propose logo

Sdd Propose

OrganizationPopular
Gentleman-Programming
sdd-propose

Create an SDD change proposal with intent, scope, and approach. Trigger: orchestrator launches proposal work for a change.

Overview

PublisherGentleman-Programming
Repositorygentle-ai
Skill namesdd-propose
Stars
7K
Forks
760
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 Gentleman-Programming on GitHub. Read the source before you install it.

Installation

Install the Sdd Propose 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/Gentleman-Programming/gentle-ai.git /tmp/gentle-ai
mkdir -p .claude/skills
cp -r /tmp/gentle-ai/internal/assets/skills/sdd-propose .claude/skills/sdd-propose
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sdd Propose 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 Sdd Propose 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 Sdd Propose 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.

Execution Role

Confirm your role before acting. You are the dedicated sdd-propose sub-agent unless you loaded this skill directly through the skill() tool.

  • If you are the sdd-propose sub-agent, continue with the phase work below. Do not delegate. Do not call the Skill tool.
  • If you loaded this skill through the skill() tool, you are the orchestrator. Stop here and delegate to the dedicated sdd-propose sub-agent using your platform's delegation primitive (for example, task(...) or a sub-agent invocation).

Language Domain Contract

Generated technical artifacts default to English. Do not inherit the user's conversational language or the active persona's regional voice for SDD artifacts unless the user explicitly requests that artifact language or the project convention requires it.

If technical artifacts are explicitly requested in another language, use a neutral/professional register unless the user explicitly requests a different tone or regional variant.

Public/contextual comments follow the target context language by default. Explicit user language or tone overrides win; otherwise use a neutral/professional register unless the target context clearly calls for another tone or regional variant.

Purpose

You are a sub-agent responsible for creating PROPOSALS. You take the exploration analysis (or direct user input) and produce a structured proposal.md document inside the change folder.

What You Receive

From the orchestrator:

  • Change name (e.g., "add-dark-mode")
  • The objective, known product decisions, and available exploration/research findings
  • Artifact store mode (engram | openspec | hybrid | none)

Execution and Persistence Contract

Follow Section B (retrieval) and Section C (persistence) from skills/_shared/sdd-phase-common.md.

  • engram: Read sdd/{change-name}/explore (optional) and sdd-init/{project} (optional). Save artifact as sdd/{change-name}/proposal.
  • openspec: Read and follow skills/_shared/openspec-convention.md.
  • hybrid: Follow BOTH conventions — persist to Engram AND write to filesystem. Retrieve dependencies from Engram (primary) with filesystem fallback.
  • none: Return result only. Never create or modify project files.
  • Never force openspec/ creation unless user requested file-based persistence or mode is hybrid.

What to Do

Step 1: Load Skills

Follow Section A from skills/_shared/sdd-phase-common.md.

Step 2: Create Change Directory

IF mode is openspec or hybrid: create the change folder structure:

openspec/changes/{change-name}/
└── proposal.md

IF mode is engram or none: Do NOT create any openspec/ directories. Skip this step.

Step 3: Read Existing Specs

IF mode is openspec or hybrid: If openspec/specs/ has relevant specs, read them to understand current behavior that this change might affect.

IF mode is engram: Existing context was already retrieved from Engram in the Persistence Contract. Skip filesystem reads.

IF mode is none: Skip — no existing specs to read.

Step 4: Write proposal.md

markdown
# Proposal: {Change Title}

## Intent

{What problem are we solving? Why does this change need to happen?
Be specific about the user need or technical debt being addressed.}

## Scope

### In Scope
- {Concrete deliverable 1}
- {Concrete deliverable 2}
- {Concrete deliverable 3}

### Out of Scope
- {What we're explicitly NOT doing}
- {Future work that's related but deferred}

## Capabilities

> This section is the CONTRACT between proposal and specs phases.
> The sdd-spec agent reads this to know exactly which spec files to create or update.
> Research `openspec/specs/` before filling this in.

### New Capabilities
<!-- Capabilities being introduced. Each gets a full spec at `openspec/changes/{change-name}/specs/<name>/spec.md` during the spec phase and becomes `openspec/specs/<name>/spec.md` at archive.
     Use kebab-case names (e.g., user-auth, data-export, api-rate-limiting).
     Leave empty if no new capabilities. -->
- `<capability-name>`: <brief description of what this capability covers>

### Modified Capabilities
<!-- Existing capabilities whose REQUIREMENTS are changing (not just implementation).
     Only list here if spec-level behavior changes. Each needs a delta spec.
     Use existing spec names from openspec/specs/. Leave empty if none. -->
- `<existing-capability-name>`: <what requirement is changing>

## Approach

{High-level technical approach. How will we solve this?
Reference the recommended approach from exploration if available.}

## Affected Areas

| Area | Impact | Description |
|------|--------|-------------|
| `path/to/area` | New/Modified/Removed | {What changes} |

## Risks

| Risk | Likelihood | Mitigation |
|------|------------|------------|
| {Risk description} | Low/Med/High | {How we mitigate} |

## Rollback Plan

{How to revert if something goes wrong. Be specific.}

## Dependencies

- {External dependency or prerequisite, if any}

## Success Criteria

- [ ] {How do we know this change succeeded?}
- [ ] {Measurable outcome}

Step 5: Persist Artifact

This step is MANDATORY — do NOT skip it.

Follow Section C from skills/_shared/sdd-phase-common.md.

  • artifact: proposal
  • topic_key: sdd/{change-name}/proposal
  • type: architecture

Step 6: Return Summary

Return to the orchestrator:

markdown
## Proposal Created

**Change**: {change-name}
**Location**: `openspec/changes/{change-name}/proposal.md` (openspec/hybrid) | Engram `sdd/{change-name}/proposal` (engram) | inline (none)

### Summary
- **Intent**: {one-line summary}
- **Scope**: {N deliverables in, M items deferred}
- **Approach**: {one-line approach}
- **Risk Level**: {Low/Medium/High}

### Next Step
Ready for specs (sdd-spec) or design (sdd-design).

Rules

  • In openspec mode, ALWAYS create the proposal.md file
  • If the change directory already exists with a proposal, READ it first and UPDATE it
  • Keep the proposal CONCISE - it's a thinking tool, not a novel
  • Every proposal MUST have a rollback plan
  • Every proposal MUST have success criteria
  • Return unresolved product decisions to the orchestrator; do not interview the user, choose for them or infer consent. Pause only dependent work, not the whole proposal for missing research metadata.
  • Use concrete file paths in "Affected Areas" when possible
  • Apply any rules.proposal from openspec/config.yaml
  • ALWAYS fill in the Capabilities section — this is the contract with sdd-spec. Research openspec/specs/ first to use correct existing capability names.
  • New Capabilities → each gets a full spec at openspec/changes/{change-name}/specs/<name>/spec.md during the spec phase and becomes openspec/specs/<name>/spec.md at archive
  • Modified Capabilities → each will become a delta spec in the change folder
  • If nothing changes at the spec level (pure refactor, config change), explicitly write "None" under both sub-sections — don't leave them as template placeholders
  • Sufficient detail: Keep the proposal concise but complete enough to explain intent, scope, risks, rollback and success criteria. Use bullets or tables where they improve clarity. Do not truncate required detail to meet a word or line cap.
  • Return envelope per Section D from skills/_shared/sdd-phase-common.md.

Frequently asked questions

What does the Sdd Propose AI skill do?

Create an SDD change proposal with intent, scope, and approach. Trigger: orchestrator launches proposal work for a change.

Why use Sdd Propose on TypingMind?

Because you install it once and use it with any model. Sdd Propose 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 Sdd Propose in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Gentleman-Programming/gentle-ai/tree/main/internal/assets/skills/sdd-propose. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Sdd Propose?

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 Sdd Propose?

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

Is the Sdd Propose AI skill free?

Yes. It is published on GitHub by Gentleman-Programming 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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