AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsnpx agentmods add skills/sickn33/agentic-awesome-skills/agy-delegateWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agy-delegate)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agy-delegate"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/agy-delegate/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agy-delegate"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/agy-delegate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 130 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 133 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.02142 |
| Opus 5 | $0.00017 | $0.01071 |
| Sonnet 5 | $0.00007 | $0.00428 |
| Haiku 4.5 | $0.00003 | $0.00214 |
Grade A, and why
agy-delegate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- agy-delegate — 100% identical, 0 lines differ
- agy-delegate — 91% identical, 35 lines differ
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Antigravity Delegate
When to Use
- You want to delegate a bounded coding task to a separate
agyimplementer (Google Antigravity) and then review its diff yourself. - The user explicitly asked for delegation to this implementer.
You are the orchestrator. This skill lets you hand a bounded coding task to a separate
implementer - the Google Antigravity CLI (agy) - then review what it produced and land it
yourself. You write the brief and own the judgment; Antigravity does the typing in its own
conversation; you verify and commit.
Nothing here is specific to one orchestrating agent. The loop needs only the ability to run a shell command and read a file, so any comparable agent can drive it. It is designed for and run on Claude Code; treat other orchestrators as designed-for, not yet proven.
When NOT to use this
- The task is small enough to just do inline - delegation overhead is not worth it.
- The
agyCLI is not installed or not authenticated. Install it from Antigravity's CLI docs and run the first-launch setup. - You want to write the code yourself, or you only need Antigravity's opinion on code you wrote (a
--read-onlydispatch covers review without edits, but a plain review may not need delegation at all).
Prerequisites (check once)
agy helpsucceeds. If not, install the Antigravity CLI and complete first-launch setup.agy modelssucceeds. That proves the CLI can authenticate and list the available model labels.- You are in (or will point
--cdat) the target git repository.
These checks do not prove that a headless write will be approved. In --print mode, Antigravity
cannot prompt for a write permission and may auto-deny it. The relay detects that denial instead of
reporting completion.
Choose the implementer model
agy has a configured default model, so --model is optional. Use it when the human has a preferred
Antigravity model label for the task. Otherwise let Antigravity use its own current default rather than
guessing.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 169 lines · 35 tokens per session scan A cff44bfc1130
agy-delegate is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,184 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 2,142 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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