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Client Compatibility

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bradygaster
client-compatibility

Platform detection and adaptive spawning for CLI vs VS Code vs other surfaces

Overview

Publisherbradygaster
Repositorysquad
Skill nameclient-compatibility
Stars
3.3K
Forks
506
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 bradygaster on GitHub. Read the source before you install it.

Installation

Install the Client Compatibility 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/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/client-compatibility
  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/bradygaster/squad.git /tmp/squad
mkdir -p .claude/skills
cp -r /tmp/squad/packages/squad-cli/templates/skills/client-compatibility .claude/skills/client-compatibility
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Client Compatibility 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 Client Compatibility 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 Client Compatibility 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.

Context

Squad runs on multiple Copilot surfaces (CLI, VS Code, JetBrains, GitHub.com). The coordinator must detect its platform and adapt spawning behavior accordingly. Different tools are available on different platforms, requiring conditional logic for agent spawning, SQL usage, and response timing.

Patterns

Platform Detection

Before spawning agents, determine the platform by checking available tools:

  1. CLI mode — task tool is available → full spawning control. Use task with agent_type, mode, model, description, prompt parameters. Collect results via read_agent.

  2. VS Code mode — runSubagent or agent tool is available → conditional behavior. Use runSubagent with the task prompt. Drop agent_type, mode, and model parameters. Multiple subagents in one turn run concurrently (equivalent to background mode). Results return automatically — no read_agent needed.

  3. Fallback mode — neither task nor runSubagent/agent available → work inline. Do not apologize or explain the limitation. Execute the task directly.

If both task and runSubagent are available, prefer task (richer parameter surface).

CopilotSession Lifecycle Invariant

  • CopilotSession lifecycle management must stay deterministic across surfaces: no ambiguous ownership or state transitions.
  • Session resources must be released on completion, cancellation, and error paths; compatibility work must not trade platform coverage for leaks.

VS Code Spawn Adaptations

When in VS Code mode, the coordinator changes behavior in these ways:

  • Spawning tool: Use runSubagent instead of task. The prompt is the only required parameter — pass the full agent prompt (charter, identity, task, hygiene, response order) exactly as you would on CLI.
  • Parallelism: Spawn ALL concurrent agents in a SINGLE turn. They run in parallel automatically. This replaces mode: "background" + read_agent polling.
  • Model selection: Accept the session model. Do NOT attempt per-spawn model selection or fallback chains — they only work on CLI. In Phase 1, all subagents use whatever model the user selected in VS Code's model picker.
  • Scribe: Cannot fire-and-forget. Batch Scribe as the LAST subagent in any parallel group. Scribe is light work (file ops only), so the blocking is tolerable.
  • Launch table: Skip it. Results arrive with the response, not separately. By the time the coordinator speaks, the work is already done.
  • read_agent: Skip entirely. Results return automatically when subagents complete.
  • agent_type: Drop it. All VS Code subagents have full tool access by default. Subagents inherit the parent's tools.
  • description: Drop it. The agent name is already in the prompt.
  • Prompt content: Keep ALL prompt structure — charter, identity, task, hygiene, response order blocks are surface-independent.

Feature Degradation Table

FeatureCLIVS CodeDegradation
Parallel fan-outmode: "background" + read_agentMultiple subagents in one turnNone — equivalent concurrency
Model selectionPer-spawn model param (4-layer hierarchy)Session model only (Phase 1)Accept session model, log intent
Scribe fire-and-forgetBackground, never readSync, must waitBatch with last parallel group
Launch table UXShow table → results laterSkip table → results with responseUX only — results are correct
SQL toolAvailableNot availableAvoid SQL in cross-platform code paths
Response order bugCritical workaroundPossibly necessary (unverified)Keep the block — harmless if unnecessary

SQL Tool Caveat

The sql tool is CLI-only. It does not exist on VS Code, JetBrains, or GitHub.com. Any coordinator logic or agent workflow that depends on SQL (todo tracking, batch processing, session state) will silently fail on non-CLI surfaces. Cross-platform code paths must not depend on SQL. Use filesystem-based state (.squad/ files) for anything that must work everywhere.

Examples

Example 1: CLI parallel spawn

typescript
// Coordinator detects task tool available → CLI mode
task({ agent_type: "general-purpose", mode: "background", model: "claude-sonnet-4.5", ... })
task({ agent_type: "general-purpose", mode: "background", model: "claude-haiku-4.5", ... })
// Later: read_agent for both

Example 2: VS Code parallel spawn

typescript
// Coordinator detects runSubagent available → VS Code mode
runSubagent({ prompt: "...Runtime Engineer charter + task..." })
runSubagent({ prompt: "...Quality Engineer charter + task..." })
runSubagent({ prompt: "...Scribe charter + task..." }) // Last in group
// Results return automatically, no read_agent

Example 3: Fallback mode

typescript
// Neither task nor runSubagent available → work inline
// Coordinator executes the task directly without spawning

Anti-Patterns

  • ❌ Using SQL tool in cross-platform workflows (breaks on VS Code/JetBrains/GitHub.com)
  • ❌ Attempting per-spawn model selection on VS Code (Phase 1 — only session model works)
  • ❌ Fire-and-forget Scribe on VS Code (must batch as last subagent)
  • ❌ Showing launch table on VS Code (results already inline)
  • ❌ Apologizing or explaining platform limitations to the user
  • ❌ Using task when only runSubagent is available
  • ❌ Dropping prompt structure (charter/identity/task) on non-CLI platforms

Frequently asked questions

What does the Client Compatibility AI skill do?

Platform detection and adaptive spawning for CLI vs VS Code vs other surfaces

Why use Client Compatibility on TypingMind?

Because you install it once and use it with any model. Client Compatibility 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 Client Compatibility in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/client-compatibility. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Client Compatibility?

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 Client Compatibility?

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

Is the Client Compatibility AI skill free?

Yes. It is published on GitHub by bradygaster 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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