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Cc Agy

Community
Dianel555
cc-agy

Delegates coding/research tasks to the Google Antigravity CLI (`agy`) for external-model execution (Gemini 3.x, Claude Sonnet/Opus 4.6, GPT-OSS). Replaces the broken `collaborating-with-gemini` skill. Use when: (1) External-model delegation via Antigravity, (2) Multi-model prototyping (switch model per call), (3) Backend/logic implementation, (4) Algorithm design and optimization, (5) Bug analysis and debugging, (6) API/database code generation, (7) Code review. Triggers: "delegate to agy", "use Antigravity", "external model", "agy", "Gemini 3.5", "Claude Sonnet 4.6", "GPT-OSS". IMPORTANT: Always request unified diff patches only. Supports multi-turn sessions via SESSION_ID.

Overview

PublisherDianel555
RepositoryDSkills
Skill namecc-agy
Stars
65
Forks
8
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Dianel555 on GitHub. Read the source before you install it.

Installation

Install the Cc Agy 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/Dianel555/DSkills/tree/main/skills/cc-agy
  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/Dianel555/DSkills.git /tmp/DSkills
mkdir -p .claude/skills
cp -r /tmp/DSkills/skills/cc-agy .claude/skills/cc-agy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cc Agy 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 Cc Agy 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 Cc Agy 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.

Quick Start

bash
python scripts/agy_bridge.py --cd "/path/to/project" --PROMPT "Your task"

Output: JSON with success, SESSION_ID, agent_messages, steps_file, and optional error / note / stderr. On failure, error names the upstream cause agy recorded (e.g. a 400/503 status) when one exists.

Parameters

usage: agy_bridge.py [-h] --PROMPT PROMPT --cd CD
                     [--model MODEL] [--SESSION_ID SESSION_ID]
                     [--sandbox] [--no-skip-permissions]
                     [--print-timeout PRINT_TIMEOUT]
                     [--return-all-messages]
                     {check,plugin} ...

Antigravity (agy) Bridge

options:
  -h, --help            show this help message and exit
  --PROMPT PROMPT       Instruction for the task to send to agy.
  --cd CD               Workspace root for agy (sets cwd + --add-dir).
  --model MODEL         Model alias (flash-low/medium/high, pro-low/high, sonnet,
                        opus, gpt-oss) or canonical string. Omit to use the
                        settings.json default.
  --SESSION_ID SESSION_ID
                        Resume a conversation by UUID. Maps to agy --conversation.
  --sandbox             Run in agy sandbox mode.
  --no-skip-permissions
                        Do NOT pass --dangerously-skip-permissions. WARNING:
                        with default toolPermission=request-review, print mode
                        WILL HANG. Only for interactive review workflows.
  --print-timeout PRINT_TIMEOUT
                        agy --print-timeout (e.g. 5m, 10m). Default 10m.
  --return-all-messages
                        Include reasoning + all type=15 steps in the response.

subcommands:
  check                 Probe agy install / version / auth / current model.
  plugin                Thin passthrough to `agy plugin list|import|install|enable|disable`.

Multi-turn Sessions

Always capture SESSION_ID from the first response for follow-up (maps to agy --conversation <UUID>, which appends to the same conversation DB):

bash
# Initial task
python scripts/agy_bridge.py --cd "/project" --PROMPT "Analyze auth in login.py"

# Continue with SESSION_ID
python scripts/agy_bridge.py --cd "/project" --SESSION_ID "uuid-from-response" --PROMPT "Write unit tests for that"

Common Patterns

Prototyping (request diffs):

bash
python scripts/agy_bridge.py --cd "/project" --PROMPT "Generate unified diff to add logging" --model pro

Switch model per call:

bash
python scripts/agy_bridge.py --cd "/project" --PROMPT "Review this Rust" --model sonnet
python scripts/agy_bridge.py --cd "/project" --PROMPT "Same code" --model opus

Setup check:

bash
python scripts/agy_bridge.py check

Manage skills/plugins (passthrough to agy):

bash
python scripts/agy_bridge.py plugin list
python scripts/agy_bridge.py plugin import /path/to/plugin

How It Works

agy --print writes nothing to stdout. The bridge instead runs agy, discovers the new conversation SQLite DB at ~/.gemini/antigravity-cli/conversations/<UUID>.db, and extracts the assistant reply from the step_type=15 rows' step_payload protobuf (field f20 → f1). MCP servers (~/.gemini/antigravity/mcp_config.json), the memory doc (~/.gemini/GEMINI.md), and skills are pre-configured by the user and auto-loaded by agy — the bridge does not manage them.

When a run fails upstream, agy writes no reply text at all and instead records the executor error in a step_type=17 row (f24 → f3: f1 user-facing line, f2 status detail). The bridge reads that row and reports the real cause — e.g. FAILED_PRECONDITION (code 400): User location is not supported for the API use. or UNAVAILABLE (code 503): No capacity available for model ... — instead of blaming its own parsing. stderr alone carries only agy's generic Agent execution terminated due to error. and no status code.

On resume, both extractors window on idx > after_idx, where the boundary spans all step types: a failed run's type=17 row lands after its last type=15 step, so a type=15-only boundary would re-attribute that stale error to the next run.

The bridge does not retry. A 400 geo rejection will almost certainly fail again on an immediate retry, and 503 capacity exhaustion is better answered by switching --model than by replaying — which could also repeat tool side effects. The structured error is passed through so the caller decides.

Security Note

By default the bridge passes --dangerously-skip-permissions to agy. This is mandatory for non-interactive --print mode because agy's default toolPermission is request-review, which blocks waiting for a human to approve tool calls — and since --print captures no TTY, the process hangs until timeout. With --dangerously-skip-permissions, agy auto-approves all tool calls. Only pass --no-skip-permissions if agy can service interactive permission prompts. The bridge always runs under a hard outer timeout (--print-timeout + 60s) so a hung agy cannot block indefinitely.

Known Limitations

  • Protobuf extraction is schema-dependent. The bridge parses agy's conversation DB without a .proto file: replies from f20 → f1 of step_type=15 rows, upstream errors from f24 → f3 of step_type=17 rows. If agy changes its internal schema, extraction returns empty. The reported error distinguishes the two cases — a message naming an upstream status means agy failed and the bridge worked; the schema-drift hint appears only when no error row explains the empty reply. Fix locations: extract_answer() and extract_run_error() in scripts/agy_bridge.py.
  • agy models returns empty on this build; model aliases are hardcoded.
  • --continue is intentionally NOT exposed (target selection is opaque); use --SESSION_ID to resume a specific conversation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cc Agy AI skill do?

Delegates coding/research tasks to the Google Antigravity CLI (`agy`) for external-model execution (Gemini 3.x, Claude Sonnet/Opus 4.6, GPT-OSS). Replaces the broken `collaborating-with-gemini` skill. Use when: (1) External-model delegation via Antigravity, (2) Multi-model prototyping (switch model per call), (3) Backend/logic implementation, (4) Algorithm design and optimization, (5) Bug analysis and debugging, (6) API/database code generation, (7) Code review. Triggers: "delegate to agy", "use Antigravity", "external model", "agy", "Gemini 3.5", "Claude Sonnet 4.6", "GPT-OSS". IMPORTANT:...

Why use Cc Agy on TypingMind?

Because you install it once and use it with any model. Cc Agy 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 Cc Agy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dianel555/DSkills/tree/main/skills/cc-agy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cc Agy?

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 Cc Agy?

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

Is the Cc Agy AI skill free?

Yes. It is published on GitHub by Dianel555 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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