Rdd Defect Workflow logo

Rdd Defect Workflow

OrganizationPopular
Gentleman-Programming
rdd-defect-workflow

Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.

Overview

PublisherGentleman-Programming
Repositorygentle-ai
Skill namerdd-defect-workflow
Stars
7K
Forks
760
Bundled files
Instructions only
LicenseApache-2.0
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 Rdd Defect Workflow 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/rdd-defect-workflow .claude/skills/rdd-defect-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rdd Defect Workflow 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 Rdd Defect Workflow 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 Rdd Defect Workflow 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.

Activation Contract

Load when the frontmatter trigger terms apply to a defect workflow.

This skill guides public collaboration. It does not grant issue approval, label, review, exception, or merge authority.

Hard Rules

  • Check the user-owned RDD kill switch first. When disabled, do not start receipt reviews or fabricate approval; follow ordinary policy and report disabled/unmanaged.
  • Require an approved issue (status:approved) and clean current main reproduction before implementation. Audit existing PRs for supersession or conflict; stop or narrow stale claims.
  • Group by causal authority invariant. Use one issue and one PR or explicit chain per independent invariant and rollback boundary. Split independent causes; never merge a superseded or conflicting authority line.
  • Inventory every operator flow claimed by the issue or PR, including entry, mode, environment, expectation, and negative controls. Require one truthful black-box bench journey per CLI or lifecycle flow, or actual runtime E2E proof when the core bench cannot represent it. Synthetic proxy coverage never proves another runtime.
  • Use CodeGraph-first impact mapping, a dedicated worktree, and behavior-first tests. Run source-mutating normalization before candidate freeze.
  • Forecast authored changes before edits. The hard limit is 400 additions plus deletions; above it, STOP for a chain or explicit maintainer-approved exception.
  • Only when RDD is enabled, bind the review candidate identity, lineage, correction, and recovery records exactly. Keep bounded review defects in one correction transaction; ordinary repository policy decides delivery.
  • Require independent read-only candidate validation before publication. Validation cannot edit source or authority; findings require a new candidate.
  • Keep communication humane and evidence-based. Repository labels and workflow metadata are maintainer-owned, never evidence of contributor blame.

Decision Gates

ConditionAction
RDD disabledOrdinary policy; disabled/unmanaged; no receipt or approval claim.
Issue gate or reproduction failsWait, stop, or narrow with evidence.
Invariant or rollback is independentSeparate issue and authoritative PR line.
Core bench fits / does not fitBench journey / actual runtime E2E; never proxy.
Forecast exceeds 400 linesChain or approved exception before edits.

Execution Steps

  1. Check mode, approval, PR conflicts, and current-main reproduction.
  2. Name invariant and rollback; isolate the worktree; CodeGraph-map code, tests, evidence, docs, distribution, and registration.
  3. Inventory flows and controls; add failing tests and the smallest correction.
  4. Normalize, enforce budget, run tests, and record each flow's exact candidate, command, scenario, and result.
  5. Freeze, validate read-only, and give the verdict, evidence, and one humane next action.

Output Contract

Return rdd_mode, issue_pr, causal_invariant, operator_flows, journey_runtime_evidence, changed_line_budget, tests, rollback, and unresolved_authority_decisions.

Identify approved and superseded/conflicting authority lines; every flow, negative control, and candidate-bound proof; additions plus deletions and chain/exception; test results; independent rollback; and unresolved maintainer decisions.

References

No supporting files. Current repository policy remains authoritative.

Frequently asked questions

What does the Rdd Defect Workflow AI skill do?

Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.

Why use Rdd Defect Workflow on TypingMind?

Because you install it once and use it with any model. Rdd Defect Workflow 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 Rdd Defect Workflow in TypingMind?

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

Which AI models can use Rdd Defect Workflow?

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 Rdd Defect Workflow?

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

Is the Rdd Defect Workflow AI skill free?

Yes. It is published on GitHub by Gentleman-Programming under the Apache-2.0 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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