ci-mockup-figure
Create space-efficient figures for papers and proposals. HTML mockups for systems, dashboards, and timelines; TikZ or skia-canvas for abstract diagrams with…
Parallel delegation fan-out. The coordinating session decomposes and integrates while task units run in parallel on workers, never on the coordinator. Sonnet is the in-session executor for anything that needs session tools. Agy (Gemini through the Antigravity CLI) takes the
$ npx -y skills add yzhao062/anywhere-agents --skill prun --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/prunContext preview
The summary Claude sees to decide when to auto-load this skill.
Parallel delegation fan-out. The coordinating session decomposes and integrates while task units run in parallel on workers, never on the coordinator. Sonnet is the in-session executor for anything that needs session tools. Agy (Gemini through the Antigravity CLI) takes the
name: prun description: Parallel delegation fan-out on Agy. The coordinating session decomposes and integrates while task units run in parallel as Agy processes (Gemini through the Antigravity CLI), never on the coordinator and never on Claude-side workers such as Sonnet subagents. Each unit runs unattended in a scratch dir or throwaway clone and gets follow-up turns while slower units finish. Codex is not a prun executor either. Unit count follows the dependency graph rather than a small fixed cap. Units may read or write code; workers never commit or push, and the session plus the user are the final integration gate.
`prun` fans a task out into independent units that run in parallel while the current session only coordinates. **Every worker is an Agy process** running Gemini through the Antigravity CLI, on the Google AI plan authenticated in `agy`. The coordinator decomposes the task, dispatches the units, gathers their results, reviews their diffs, and integrates. It never runs a unit itself.
**No Claude-side workers.** A Sonnet subagent, a Workflow agent, or any other Agent-tool worker draws on the same Claude account as the coordinating session, so a fan-out of them spends that account's quota at the rate of the fan-out. That is the pool the coordinating session itself needs, and it drained fast once `prun` routed units to Sonnet. **Codex is not a prun executor** either; its higher-cost quota is reserved for the default `/vet` gatekeeper role. Exact plan buckets can change, so inspect current Agy quota before a large batch.
The native Workflow tool fans a task out across **Claude** subagents under a deterministic script, with structured output, judge panels, and resume. A Workflow run counts against the Anthropic plan's usage and rate limits, and its agents use the session model unless the script routes a stage to a different Claude model.
`prun` is the fan-out that stays off that account. Its units run on Agy and use the Google AI plan; the coordinating session spends only the small Anthropic amount it needs to decompose, dispatch, read results, and integrate. `prun` therefore never starts a Workflow or a Claude subagent, not as a unit, a fallback, or a second panel. When the user explicitly asks for a Claude panel, that is a Workflow run the user asked for, and it happens outside `prun`. A cross-vendor read on staged work is what `/vet` is for.
When the Agy Gemini group cannot accommodate the next batch, queue or defer units instead of moving them onto the Claude account. Read the meter with `agent-quota`, including snapshot age and reset times, and do not silently shrink a genuinely parallel task to an arbitrary two or three workers. The dispatcher's own quota route, described under dispatch-task usage, already stops a unit from launching into an empty group.
Use `prun` when the task splits into **independent units that can run at once** (different modules, separate research questions, parallel analyses). Units may be heterogeneous, and there can be **many of them**: a dozen or twenty in parallel is normal when the task warrants it.
Do not use `prun` when the task is one sequential unit, or units depend on each other's output, or a unit's result cannot be checked without redoing it.
| Executor | Quota | Notes | |---|---|---| | Agy (`agy`) | Google AI plan authenticated in Antigravity | **The only worker.** Gemini 3.8 Flash High at `high` effort; fast, separately funded, and dispatched with full unattended tool permission inside a scratch dir or throwaway clone. | | Claude session (this session) | Current Claude account; check Settings > Usage for the applicable limits or credits | Coordinator and integrator only, on whatever model is selected. Never a unit. |
Rules:
units in a throwaway clone all go through `dispatch-task-agy`. The dispatcher gives a unit the same unattended capability as the `/vet` Agy reviewer, so it can verify numbers, run experiments, and fetch the web. Agy defaults to `gemini-3.8-flash-high` at the CLI's maximum `high` effort.
or a Workflow agent for a unit, including as a fallback when the Agy pool is short. Those workers spend the coordinating session's own Claude account. When Agy cannot take a batch, queue it or tell the user.
role. Do not route a prun unit to `codex exec`, even if a legacy dispatcher remains on disk for compatibility with old state directories.
MCP, email connectors, or Artifact tool. Gather what a unit needs from those tools in the coordinating session before dispatch, and put it in the unit prompt; leave a small action that needs them to the coordinator as one inline step. A task whose substantive work needs those tools throughout is not a `prun` task.
while others are still running, dispatch a follow-up unit rather than idling, provided the follow-up discharges real work: an acceptance criterion the result left open, a claim it made without evidence, a source it cited but did not fetch, a check it proposed but did not run, or the next independent unit in the queue. A slower sibling is not by itself a reason to invent work. `--continue-from <state-dir>` resumes the same conversation, so the follow-up keeps the earlier context; a fresh prompt with a fresh result path is the alternative. Record each follow-up in the ledger like any other unit.
One config for every agent — Claude Code, Codex, and whatever comes next. Start with effective defaults. Add packs, small bundles of rules, skills, or permissions, as you need them. One AGENTS.md drives every agent in every repo on every machine.
Repo: yzhao062/anywhere-agents
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