Agent Skills: [DELEGATE_AGY]

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UncategorizedID: bsamiee/parametric_forge/delegate-agy

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pnpm dlx add-skill https://github.com/bsamiee/Parametric_Forge/tree/HEAD/.claude/skills/delegate-agy

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.claude/skills/delegate-agy/SKILL.md

Skill Metadata

Name
delegate-agy
Description
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[DELEGATE_AGY]

Antigravity is an external Gemini call admitted only where it adds capability beyond the local toolchain. Print mode runs the wrapper — one bounded prompt in, one JSON receipt out — yet executes tools and lands file writes without any permission flag, so safety is prompt discipline: a review or judgment prompt names no save path and directs inspect-only work; a generation prompt binds every save path to a throwaway scratch root, never a repo path or $HOME.

[01]-[ROUTING]

[SCRIPTS]:

  • [01]-RUNNER: wraps the CLI this skill invokes; carries prompt and models subcommands.

[02]-[CAPABILITY]

| [INDEX] | [TRIGGER] | [WHY_GEMINI] | | :-----: | :---------------------------------------------------------------- | :------------------------------------------------ | | [01] | Screenshots, generated images, UI states, visual diffs, diagrams | Native multimodal judgment over --add-dir files | | [02] | Critique or red-team stage wanting an independent second reviewer | Read-only findings from a different model lineage | | [03] | Image generation, mockup and diagram iteration | Native generate_image rendering (Nano Banana) | | [04] | Competing designs, ambiguous tradeoffs, long-context synthesis | Independent perspective outside the main context | | [05] | Vague requirements needing constraints and edge cases | Ambiguity reduction as a separate pass | | [06] | Counterexamples, risk inventories, blind spots on gathered facts | Adversarial second reading | | [07] | Redacted log or dataset distillation in a scratch directory | Pattern finding without polluting main context | | [08] | Explicit requests for Gemini, Antigravity, or Google Ultra | User-directed routing |

[03]-[MODEL_POLICY]

Wrapper defaults pin the strongest Gemini reasoning model at its highest tier; that pin is the carrier of a standing operator policy, never a tunable preference. Agents never choose models in ordinary use; models lists the live catalog for capability accounting and skill maintenance.

[04]-[INVOCATION]

Run from this skill directory:

uv run scripts/agy.py models
uv run scripts/agy.py prompt "Compare these two approaches and return the top 3 tradeoffs." --timeout 5m
uv run scripts/agy.py prompt "Assess the screenshot at /abs/path/shot.png and return concrete UI defects." --add-dir /abs/path --timeout 10m

Both halves bind the multimodal contract: --add-dir grants the bounded directory, and the prompt names each file by ABSOLUTE path — a granted directory with a bare filename in the prompt resolves nothing. --add-dir grants only directories that answer the prompt, and the only writes a wrapper prompt ever requests are generation artifacts under a scratch root.

--log-file routes the CLI log to an explicit path; a sandboxed or scratch-rooted environment passes a writable scratch path there instead of relying on the default log location. AGY_BIN overrides the binary path (default agy), AGY_MODEL overrides the pinned model, AGY_LOG_FILE sets the default log path, and AGY_PRINT_TIMEOUT overrides the default 5m timeout.

Each prompt run returns one JSON receipt:

{"op":"prompt","output":"..."}
{"op":"prompt","fault":"auth_required","detail":"..."}

scripts/agy.py owns the fault vocabulary the receipt's fault field carries: a new failure class is one _Fault row with its classifier tokens, and an unmatched failure classifies as process_error. auth_required resolves through interactive agy in a real TTY with Google OAuth as the account holding the Antigravity subscription.

[05]-[PROMPT_CONTRACT]

  • State the task, its context, and the exact output shape in one self-contained prompt; Antigravity sees only what that prompt carries.
  • Carry the constraints that bind the answer: audience, files already inspected, limits, and facts not to assume.
  • Ask for ranked options, deltas, typed findings, or a direct answer; open-ended commentary is never the request.

[06]-[REVIEW]

A second-perspective review runs bounded critique and red-team: freeze the evidence, invert the objective, demand falsifiable findings. It inverts the every-agent-writes law at exactly this boundary — the Gemini reviewer inspects and returns typed findings, and a Claude writer adjudicates each finding against source before applying the fix; the repair rail never crosses to the reviewer.

  • [EVIDENCE]: Subject arrives frozen — exact files under --add-dir, invariants under test, executed check output, known constraints.
  • [CONTAMINANT]: A conversation transcript and a producer's self-justification never reach the reviewer.
  • [OBJECTIVE]: Prompt directs disproof — violated invariants, omitted consumers, false assumptions, failure paths, visual-contract breaks.
  • [BURDEN]: Work stays naive until it survives the attack, so a clean verdict is earned by an attack that finds nothing.
  • [FINDINGS]: Each finding carries {severity, invariant, evidence, failure_path, minimal_fix}.
  • [REJECTED]: Praise, style preference, and ungrounded speculation are shapes the prompt names rejected.
  • [ADJUDICATION]: Claude re-derives each finding from disk, fixes true positives at the root, and refutes false ones with source, never by vote.
uv run scripts/agy.py prompt "ROLE: read-only adversarial reviewer. SUBJECT: /abs/path/target. INVARIANT UNDER TEST: <invariant>. AUTHORITY: inspect only; propose, never edit. OUTPUT: a JSON array of findings only, each {severity, invariant, evidence, failure_path, minimal_fix}; reject praise, style preferences, and ungrounded speculation. Return [] only if a real attack finds nothing." --add-dir /abs/path --timeout 5m

[07]-[GENERATION]

Image generation is the default agent's built-in generate_image tool, fired from inside an ordinary print-mode prompt — no CLI flag, subcommand, plugin, or models row invokes it. Every generation prompt carries three obligations: name the tool and forbid code-drawing (an unnamed request lets the agent fall back to scripting Pillow when the render fails), state the visual spec, and give an absolute save path under a scratch root the caller creates. Each render also persists as <image_name>_<epoch-ms>.jpg under ~/.gemini/antigravity-cli/brain/<conversation-id>/.

uv run scripts/agy.py prompt "Use your generate_image tool (never code-drawing) to generate: <visual spec>, aspect ratio 16:9. Save to /abs/scratch/name.png." --add-dir /abs/scratch --timeout 5m

Prompt prose carries everything; the agent maps it onto tool parameters: Prompt, AspectRatio (1:1 default at 1024x1024; 2:3, 3:2, 3:4, 4:3, 9:16, 16:9 — 16:9 renders 1376x768), ImagePaths (up to 3 absolute paths to edit, combine, or reference — the edit modality: name the source by absolute path, state the change), and ImageName.

No tier selector exists in tool schema, CLI flags, or model catalog: the backend serves Nano Banana Pro where the account has access, Nano Banana otherwise; --model picks only the reasoning agent driving the tool.

Every render passes two gates. magick identify proves a real raster at the expected dimensions — the payload is JPEG whatever the extension unless the agent converts, so the filename is never format proof — and a wrapper read-back describes the artifact against the visual contract. A ~1KB file is the failure signature: the backend returned no image (CORTEX_STEP_TYPE_GENERATE_IMAGE: no image generated in response in the --log-file) and the agent code-drew a placeholder; the never-code-drawing clause and the size gate catch it, and one re-run resolves a transient backend miss.

Generated mockups and diagrams are inputs to the realizing skill, never deliverables: agy drafts the spec, renders, and read-back-critiques, then mermaid-diagramming realizes the fence. A closed loop is the strongest pattern — visual contract, render, read-back critique against the contract, targeted correction — never a single "make it pretty" round.

[08]-[REFUSAL]

  • [SECRETS]: OAuth codes, tokens, credential files, and unredacted sensitive logs never enter a prompt.
  • [AUTHORITY]: Facts owned by local source, official docs, MCPs, or repo commands come from those owners, never from Antigravity recall.
  • [ROUTINE]: Edits, formatting, git operations, package upgrades, and checks the local toolchain owns stay local.
  • [SCOPE]: prompt and models are the wrapper's only surface; agent selection, background tasks, and shell-login subcommands stay outside it.

Interactive agy in a real TTY owns the outside surfaces — ongoing conversations, workspace tool permissions, resume, plugin management, sandboxed project work; agy --help is the flag and subcommand contract. gsd-* personas are interactive-runtime composition only: they hang under plain print mode and emit process narration rather than bounded answers under --mode plan, so a bounded one-shot runs the default agent with a strong prompt, never a gsd persona.

GSD's artifact pipeline — mapper, researcher, planner, checker, executor, verifier — composes inside a live session where each role consumes only the prior role's artifact.