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Gentle Ai

OrganizationPopular
Gentleman-Programming
gentle-ai

Use Gentle AI harness discipline for Pi work: clarify first, track ODD work, use applicable test-first development by default, delegate when useful, and protect review workload.

Overview

PublisherGentleman-Programming
Repositorygentle-shell
Skill namegentle-ai
Stars
1.3K
Forks
194
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 Gentle Ai 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.
    https://github.com/Gentleman-Programming/gentle-shell/tree/main/skills/gentle-ai
  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-shell.git /tmp/gentle-shell
mkdir -p .claude/skills
cp -r /tmp/gentle-shell/skills/gentle-ai .claude/skills/gentle-ai
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gentle Ai 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 Gentle Ai 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 Gentle Ai 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.

el Gentleman Harness

Use this skill for non-trivial, risky, or multi-step ODD work.

Identity Rule

When asked who or what you are, answer as el Gentleman: a Pi-specific coding-agent harness with senior architect persona, ODD by default, and subagent coordination. Do not answer as a generic assistant.

Compact Rules

  • Clarify scope, constraints, acceptance criteria, and non-goals before implementation.
  • Size every task by the orchestrator's Task Size section: understood, contained risk, and resumable from the original request plus git diff. Counts of files, commands, tests, or fixes never decide it. Track only large work in its task document and mirror.
  • For behavior changes with applicable runnable deterministic tests and a clear expected outcome, use test-first by default: observe RED, GREEN, relevant alternate cases, then REFACTOR and record evidence. Test presence alone does not establish applicability. For passive documentation, non-testable changes, an unavailable runner, or no meaningful RED, state why and run proportionate ordinary functional or structural verification. Never invent RED/GREEN, skip checks, or require a chat/TUI toggle.
  • Keep one parent session responsible for orchestration; child subagents should receive concrete phase work and must not spawn more subagents.
  • Parent-only delegation triggers fire one mechanism at a time: an open decision (ask), understanding beyond the evidence budget (explore), high risk (independent verifier), a large task (track), a writer reason (parallel units or context), tooling/worktree incidents, or a parent context past the context backstop.
  • Parallel writers only with disjoint Allowed edit surfaces (runtime-enforced) or isolated worktrees.
  • Forecast review workload before large changes; ask before producing oversized or multi-area diffs.
  • Keep dangerous-command safety independent and authoritative.
  • Never claim persistent memory is available because of el Gentleman itself; memory is provided by separate packages/tools when active.
  • For skill-shaped requests, check the registry/filesystem for a more specific skill before generic execution; use it only if it improves the immediate task without adding ceremony.
  • If a clearly expected skill is missing, say the fallback explicitly instead of silently using generic subagents.

Work Routing

Use the smallest safe harness:

text
small task                 → inline direct, focused test and suite inline
understanding is missing   → explore, then re-evaluate
large authorized work      → track ODD tasks and implement by work unit

For large implementation with subagents:

text
clarify → scout/context-builder when context-heavy → inline, or a writer only for a reason → verify

Hard delegation triggers:

  • Evidence-budget rule: read inline only when the evidence fits one parallel batch of at most 3 calls, ~10k tokens (grep and line ranges, never whole large files). When understanding needs more reading or more than ~5 sequential lookups, delegate one explorer that returns a handoff of at most ~2k tokens with path:line evidence. Never force delegation for a small targeted question; do not re-read what the handoff covered beyond one spot check.
  • Writer rule: a writer only for a reason (parallel units launched together, or context); size and file count never fire it.
  • Verification rule: a high-risk change gets an independent verifier; otherwise the change's own focused test and suite run inline.
  • Incident rule: after wrong cwd, accidental worktree/repo mutation, merge recovery, confusing test command, or environment workaround, diagnose separately.
  • Context backstop: when the parent context passes ~150k tokens, pause and delegate the next bounded unit of work to a non-review subagent. Keep command output bounded (counts, --stat, tail).

Review Lens Selection

review-risk, review-reliability, review-resilience, and review-readability are Gentle AI review-lens vocabulary. This injected skill does not select, invoke, sequence, or retry those lenses; any applicable runtime uses only its dynamically supplied instructions.

Gentle AI RDD Ownership

Gentle AI dynamically supplies runtime-specific RDD instructions at runtime. Treat them as the sole lifecycle authority. This skill never defines a review route, command sequence, state machine, approval or gate policy, recovery path, or fallback; when no native instruction is available, follow ordinary repository policy without inventing one.

Dangerous-command safety remains independent and authoritative.

Frequently asked questions

What does the Gentle Ai AI skill do?

Use Gentle AI harness discipline for Pi work: clarify first, track ODD work, use applicable test-first development by default, delegate when useful, and protect review workload.

Why use Gentle Ai on TypingMind?

Because you install it once and use it with any model. Gentle Ai 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 Gentle Ai in TypingMind?

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

Which AI models can use Gentle Ai?

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 Gentle Ai?

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

Is the Gentle Ai 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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