# Method Figure

> Generate a publication-grade method / architecture / pipeline / workflow figure (a paper or README 'Figure 1') as an AUDITABLE object, not a one-shot prompt. A deterministic JSON blueprint LOCKS the content; an image model (gpt-image-2, baked by the agent via mcp__codex__codex — Codex GPT-5.5 xhigh, sandbox workspace-write) bakes the aesthetic from a labeled-condition render + the project's real…

- **Type:** Skill
- **Install:** `agentstack add skill-wanshuiyin-aris-movie-director-method-figure`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [wanshuiyin](https://agentstack.voostack.com/s/wanshuiyin)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [wanshuiyin](https://github.com/wanshuiyin)
- **Source:** https://github.com/wanshuiyin/ARIS-Movie-Director/tree/main/skills/method-figure
- **Website:** https://wanshuiyin.github.io/ARIS-Movie-Director/comic/

## Install

```sh
agentstack add skill-wanshuiyin-aris-movie-director-method-figure
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# method-figure

Turn "draw our method figure" from a one-shot gamble into the **same audited spiral the framework uses for
comics**: a blueprint is the source of truth, the image model bakes the look, a cross-model panel + a
deterministic diff keep it honest, and the loop converges to a publication-grade figure that is
**reproducible** (re-run the blueprint) and **auditable** (a trace of every round).

Two things are simultaneously true: (a) gpt-image-2 CAN render a clean Figure-1 with legible labels when
*conditioned on a labeled blueprint* — do not assume it garbles text; (b) on a free prompt it DRIFTS
(renames phases, invents nodes, garbles a token, leaves pasted-looking floating labels). The blueprint +
blind-transcribe-then-hard-diff loop turns (a) into a reliable result and catches (b) every round.

```text
  system description ─▶ ① BLUEPRINT (JSON content-lock)  ── validate_blueprint.py
                              ▼
                        ② CONDITION (white-bg labeled SVG → PNG) + identity sheet (real chibi, optional)  ── render_condition.py --png
                              ▼
                        ③ BAKE  — agent: mcp__codex__codex(prompt+abs ref paths+out_path, workspace-write, gpt-5.5, config{xhigh}) → gpt-image-2 native PNG  ── pickup_image.py --out-existing (sig+size+dims, mtime-bound, HARD-VETO struct/zlib/PIL/SVG, fail-closed)
                              ▼
                        ④ PANEL — Gemini ‖ Codex BLIND-transcribe → content_diff.py (observed ⊖ blueprint) → Claude structural sign-off
                              ▼
                        ⑤ agent reads the diff + the panel blockers → re-bake re-asserting the locked labels
                              ▼
                   converged? ─ no ─▶ ③   (bounded: max_rounds → escalate to human)
                              │ yes
                              ▼
                        ⑥ APPROVE → figure.png + blueprint.json + trace.jsonl
```

## Constants
- **GENERATOR** = Codex `gpt-5.5`, `config: {model_reasoning_effort: xhigh, include_image_gen_tool: true}` → the native `image_generation`
  tool (gpt-image-2). **CRITICAL**: image_gen is produced ONLY via **`mcp__codex__codex`** (the agent tool), NOT
  `codex exec`. `codex exec` / over-specified / forbid-list prompts make Codex hand-draw a code fallback
  (struct+zlib PNG or SVG/matplotlib) — visually indistinguishable for trivial shapes, useless for a real
  method-figure. The working invocation is **`mcp__codex__codex`** with a **dead-simple** prompt +
  `sandbox: "workspace-write"` (it must WRITE the out_path) + `model: "gpt-5.5"` +
  `config: {model_reasoning_effort: "xhigh", include_image_gen_tool: true}` (the schema has NO top-level effort
  param; `config{xhigh}` shorthand below ALWAYS expands to **both** these keys — without `include_image_gen_tool`
  codex won't fire its native image tool, it falls back to descriptive text / an SVG renderer) + `cwd: `.
  Reference images are passed by **absolute file path inside the prompt** (the schema has NO `-i`); the output
  path is a **deterministic abs path** in the prompt. Pick it up with **`pickup_image.py --out-existing`**
  (verifies the EXPLICIT out_path: PNG sig + size + dims, `mtime >= request.created_at`) which **HARD-VETOES**
  struct/zlib/PIL/``/matplotlib markers in the agent transcript (fail-closed; there is **no** 'native sig
  wins' override). **Honesty caveat:** as of Jun 2026 native headless persistence is unreliable, so this
  fail-closed verifier — not any `sandbox` setting — is the first guard against a non-native bake. But the
  HARD-VETO is a **BEST-EFFORT denylist** against the *known* codex-exec hand-draw fallback (struct/zlib/PIL/
  SVG/matplotlib markers), **NOT a complete security boundary** — a novel fallback that emits a sig-valid PNG
  without those markers can slip past it. The **load-bearing faithfulness gate is the cross-model blind-transcribe
  panel + the deterministic `content_diff`** (the pixels are what reviewers transcribe), with this denylist as a
  cheap upstream filter.
- **PANEL** (automated blind-transcribe) = `mcp__gemini-cli__ask-gemini` (`auto-gemini-3`) + `mcp__codex__codex`
  (gpt-5.5 xhigh) + the deterministic `content_diff`. **Claude (this agent) is the post-pass STRUCTURAL sign-off,
  not a blind transcriber** — the loop converges on Gemini-approve + Codex-no-veto + empty-diff, then Claude signs off.
- **CROSS-MODEL ACQUITTAL** — Codex is the generation family, so a Codex `approve` can only *diagnose/veto*,
  never be the sole acquitter. ACCEPT requires **Gemini approve + Claude structural approve + the hard-diff empty**.
- **MAX_ROUNDS** = 4, then escalate to human with best-so-far + open blockers.
- **LABEL_POLICY** = **`baked` only in v0** — the image model renders ALL text; nothing is hand-pasted.
  (`hybrid`/`overlay` — lock structure + vector-overlay the labels for paper zero-tolerance text — are on the
  v1 roadmap; do NOT use a vector overlay as an ad-hoc patch on a finished bake, it reads as pasted.)
- **OUTPUT_DIR** = `figures/method_figure//` (figure.png, blueprint.json, condition.svg, trace.jsonl).
- **NATIVE-IMAGE FAIL-CLOSED** — accept a bake ONLY if a real native PNG exists at the **explicit out_path**,
  sha/size/dims check out and `mtime >= request.created_at`, and the agent transcript shows **no** struct/zlib/
  PIL/``/matplotlib fallback (`pickup_image.py --out-existing`, HARD-VETO — a clean sig never overrides a
  fallback marker). This veto is a **BEST-EFFORT denylist** against the *known* codex-exec hand-draw fallback,
  **NOT a complete security boundary** (a novel marker-free fallback could evade it). The load-bearing
  faithfulness gate remains the **cross-model blind-transcribe panel + the deterministic `content_diff`**; the
  denylist is a cheap upstream filter that matters because native headless persistence is currently unreliable.
- **SERIALIZE BAKES** — never run two image generations at once. The default `--bake-mode=agent` writes each
  native PNG to its **explicit per-round `out_path`** (no shared dir), so concurrent agent bakes still risk a
  request/status sidecar race — keep one runner per figure. (The global `~/.codex/generated_images` dir +
  newest-after-marker pickup that could cross-pollinate concurrent bakes is a hazard of the **LEGACY
  `--bake-mode=exec` path ONLY**, which is retired for real bakes.)

## Input contract / ARIS hand-off (who decides WHAT, who only renders)
This skill is **pure render + verify**. Ownership:
- **Upstream owns the semantics** — what to depict, the labels, the graph, the grouping, the headline
  claim/number, the identity refs. method-figure does NOT choose content and **must not invent** a node,
  claim, number, or method structure (if one is missing it ESCALATES, it does not make it up).
- **Step-0 is now DETERMINISTIC** — `run_spiral.py` calls [`scripts/compile_brief.py`](scripts/compile_brief.py)
  to map a `method_figure_brief.json` → a schema-valid `blueprint.json` + `traceability.json`, fail-closed (an
  object that can't trace to a brief field, or a missing claim/number/trait, is refused — not invented). It is
  no longer a manual LLM hop. Full field map + the guards: `references/blueprint_authoring.md`.
- **method-figure owns** validation → condition render → image bake → cross-model panel → diff → retry, and
  has VETO power: it returns `FAILED / Logic Drift` rather than ship a figure whose pixels contradict the blueprint.

**The default single input** = a **`method_figure_brief.json`** (`schemas/method_figure_brief.schema.json`) —
ONE ARIS-format file; the blueprint, the coordinates, and the identity wiring are all derived. The identity
sheet is resolved from the brief's `identity_refs[].path` (no separate `--identity` to manage). **Where the
input comes from**, in authority order:
1. **a `method_figure_brief.json`** — the canonical ARIS hand-off (what `paper-plan` emits); auto-detected + compiled. ·
2. an existing hand-tuned `blueprint.json` — power-user override (`--from-blueprint`, used as-is). ·
3. an `experiment-plan` / `paper-write` method section / free-text — no brief yet: the agent first DRAFTS a
   `method_figure_brief.json` from it (claims/numbers verbatim; anything missing → Refuse-and-Escalate), then compiles.

**ARIS integration:** the canonical producer is **`paper-plan`** — after its `claims_matrix` it emits the
`method_figure_brief` (components, flows, phases, the headline claim/number, identity refs, `forbidden_tokens`).
You feed that **one file** to `run_spiral.py`; Step-0 compiles it and the traceability is enforced by the
compiler (an un-traceable object is a Refuse-and-Escalate, not a render). The identity sheet is created once
upstream and locked; method-figure only reads it.

## Fast path — one command (single input: a brief)
Feed ONE `method_figure_brief.json`; the whole loop is one command:
```bash
python3 scripts/run_spiral.py your_method_figure_brief.json --out-dir figures/method_figure/
#  auto-detects a brief → Step-0 compile_brief.py → blueprint.json + traceability.json (deterministic, fail-closed)
#  → validates → renders condition(+png) → [bake (agent: mcp__codex__codex --bake-mode=agent, workspace-write,
#  gpt-5.5 config{xhigh} → gpt-image-2 native PNG via the .bakereq.json sidecar) → pickup_image.py --out-existing
#  verify (fail-closed, HARD-VETO over the status file's mcp_output) → Gemini + Codex blind-transcribe → content_diff → blockers] × rounds
#  → on PANEL-CLEAN writes figure.png + blueprint.json + traceability.json + trace.jsonl.
#  input auto-detect: brief (components+flows) vs blueprint (version) vs ambiguous → fail-closed (--from-brief/--from-blueprint)
#  --identity is OPTIONAL (resolved from the brief's identity_refs[0].path);  --dry-run prints the round-1 bake
#  prompt;  --p0-only runs the zero-credit gate (validate+compile+render) then stops;  --max-rounds N;  --effort high|xhigh.
```
> **Power-user / override:** already have a hand-tuned blueprint? `run_spiral.py blueprint.json --identity
> sheet.png --out-dir … --from-blueprint` runs the legacy path unchanged. A worked example brief lives at
> [`examples/method_figure/method_figure_brief.json`](examples/method_figure/method_figure_brief.json).
Long-running (each bake ~3-8 min) — run it in the background; watch `trace.jsonl`. It converges to
**PANEL-CLEAN** — BOTH reviewers returned parseable JSON, **Gemini approve AND Codex approve**, the
deterministic `content_diff` empty, core scores (incl. `character_identity` when an identity sheet is given)
≥ threshold, and no anomalies/blockers — then STOPS and hands to the calling agent (Claude) for the final
**structural** sign-off (the generator family never self-acquits). The manual steps below are exactly what
`run_spiral.py` automates (run them to debug one stage).

## Who runs `--bake-mode=agent` (the agent-wrapper SOP) — REQUIRED for the default mode to function
The bake is a **synchronous sidecar handshake** and the **skill agent** is its fulfiller (without it, every bake
polls to `--bake-timeout` and escalates with `failure_kind="other"` — fail-closed, not a hang, never a false throttle):
1. Launch the orchestrator in the **BACKGROUND**:
   `python3 scripts/run_spiral.py your_brief.json --out-dir figures/method_figure/ --bake-mode agent`.
2. **Loop** until it prints PANEL-CLEAN / escalates / exits:
   - watch `/` for a new `*.bakereq.json` (the orchestrator writes `round.png.bakereq.json`);
   - read it; call `mcp__codex__codex` with **exactly** its
     `{prompt: , model:"gpt-5.5", config:{include_image_gen_tool:true, model_reasoning_effort:"xhigh"}, sandbox:"workspace-write", cwd:}`
     (codex writes the native PNG to the sidecar's `out_path`). The `config` MUST carry **both**
     `include_image_gen_tool:true` AND `model_reasoning_effort:"xhigh"`: without `include_image_gen_tool` Codex will
     **not** fire its native `gpt-image-2` tool (it falls back to a struct/zlib/SVG hand-draw), and `xhigh` is the
     required reasoning tier;
   - then read `request_id` from the `*.bakereq.json` and write `.bakestatus.json` carrying **the status, a
     bounded raw `mcp_output`, AND that `request_id` VERBATIM** — `mcp_output` so the HARD-VETO can scan it (the core
     feeds this file to `pickup --transcript`; an `ok` status with no raw output makes the veto INERT), and
     `request_id` because `pickup_image.py --out-existing --request-id` **fail-closes the bake if the status
     `request_id` is missing or mismatched** (write it on BOTH ok and fail):
     `{"status":"ok","mcp_output":"","request_id":""}`, or
     `{"status":"fail","failure_kind":"throttle","mcp_output":"","request_id":""}` on a
     429 / `MODEL_CAPACITY_EXHAUSTED` / overloaded error (else
     `{"status":"fail","failure_kind":"other","mcp_output":"","mcp_error":"","request_id":""}`).
3. The core proceeds to verify ONLY on `status:"ok"`, via `pickup_image.py --out-existing` (sig + dims + size >
   500000 + `mtime >= created_at`, HARD-VETO over `mcp_output`, and `--request-id` fail-close if the status
   `request_id` is absent/mismatched). `--bake-mode=exec` is the legacy/CI non-image path and RAISES if it reaches a real bake.

## Workflow (what run_spiral.py automates — or run by hand)

### ① Author the BLUEPRINT (content lock)
Write `blueprint.json` per `schemas/blueprint.schema.json`. The `*_exact` fields (`label_exact`, `desc_exact`,
group/edge/callout `*_exact`, `rail.label_exact`) are the **LOCKED text re-asserted verbatim every round**;
`expected_tokens[]` are what the panel must blind-transcribe and the diff checks. Then:
```bash
python3 scripts/validate_blueprint.py blueprint.json   # jsonschema (if installed) + unique ids · edges resolve · box/group/callout bounds · no dup labels
```

### ② Render the CONDITION
```bash
python3 scripts/render_condition.py blueprint.json --out condition.svg --png condition.png   # white-bg labeled layout → rasterized
```
Prepare `identity_sheet.png` from the project's REAL characters if the figure has any (never invent robots).
The condition PNG + the identity sheet are the two image references.

### ③ BAKE (round N) — agent seam
Call `mcp__codex__codex` (sandbox **workspace-write** — it must WRITE the out_path; `model: gpt-5.5`,
`config: {model_reasoning_effort: xhigh, include_image_gen_tool: true}`, `cwd: `) with the prompt from
`references/prompt_templates.md §A` — it RE-ASSERTS every `*_exact` label + the round-N blockers + the carried
`positive_invariants`, with `condition.png` + `identity_sheet.png` referenced by **absolute path inside the
prompt** (the schema has no `-i`) and the **exact out_path** to save the native PNG. Write the bake status to
`round.png.bakestatus.json` carrying the raw `mcp_output` (so the HARD-VETO can scan it) **AND the
`request_id` copied VERBATIM from `round.png.bakereq.json`** (pickup `--request-id` fail-closes if it's
missing/mismatched), then verify the explicit out_path (no marker/glob):
```bash
python3 scripts/pickup_image.py --out-existing --out figures/method_figure//round.png --min-bytes 500000 --aspect  --created-at  --request-id .png.bakereq.json> --transcript figures/method_figure//round.png.bakestatus.json
```

### ④ PANEL — blind transcribe, then hard diff
Ask each reviewer (`references/prompt_templates.md §B`) for the STRICT JSON of
`references/reviewer_protocol.md` — they transcribe `observed_tokens` / `observed_edges` / `identity_audit`
and an `anomalies` list (the **Negative-Space Audit**), NOT shown the expected labels. Save as
`round.{cc,gemini,codex}.json`, then:
```bash
python3 scripts/content_diff.py blueprint.json round.cc.json round.gemini.json round.codex.json
# → missing_tokens / unaccounted_tokens / anomalies ; empty == content-accurate
```

### ⑤ Decide (stop rule) — the agent consolidates
Read the diff report + the three reviewers' `blockers`. The executing agent itself merges **blockers only**
(ignore `nice_to_have` — chasing polish makes it oscillate), carries the unio

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [wanshuiyin](https://github.com/wanshuiyin)
- **Source:** [wanshuiyin/ARIS-Movie-Director](https://github.com/wanshuiyin/ARIS-Movie-Director)
- **License:** MIT
- **Homepage:** https://wanshuiyin.github.io/ARIS-Movie-Director/comic/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-wanshuiyin-aris-movie-director-method-figure
- Seller: https://agentstack.voostack.com/s/wanshuiyin
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.
