Illo

Make original, distinctive editorial illustrations for written content. One image explains one idea: a key judgment, a flow, a before/after, a trap, a loop. A recurring mascot is the one performing the idea in every scene — the subject, never decoration. When one idea advances through stages, it can be a mini-comic: 2–4 panels inside a single image. And when the idea is itself a traceable structure — a pipeline, labeled stages, a fan-out, a timeline, a loop — it can be an explainer: the same mascot and look drawing the structure as a hand-built sketch-diagram with arrows and callouts (references/composition.md, "Two registers" and "Pick the diagram type"; editorial scene is always the default). A named pipeline or recipe is labeled stages inside that register — named phases in order, one connected system, pack-solved for this body, never a new look. Or a character cutout: the mascot alone on a transparent PNG for downstream overlay — pose and contact continuity only, no idea, no text, no environment (references/cutout.md).

This is a configurable house style, not a generic image generator. The methodology is the constant; the character pack and palette are the parameters — and a character pack carries its style with it: one look per pack, chosen from the bundled look library (riso — grainy halftone, ink-layer offset, paper grain, one bold softly-rounded outline — plus blueprint, woodcut, pixel, clay, manila, chalk, phosphor, enamel, gouache, felt, diorama, sketchbook, bricks, fizz, bloom, and snes) or a custom style file. The default mascot is Blot, a deadpan ink-drop in riso. Palettes come from presets, the user's own palette file, or one derived color. Whatever the parameters, it is intentionally not a photo — with one deliberate exception, the bricks look, a toy-brick photography style — not a logo, not a corporate infographic, not a formal boxes-and-diamonds flowchart look, not a UI mockup. Asking for a flowchart still means labeled stages in the pack's look — the formality ban is a look constraint, not a refusal of the word.

Use cases — route the request

Prerequisites

The engine (scripts/illo.py, stdlib Python, no installs) renders through one of three engine backends; python3 and network access are the only hard requirements. Grok Bot (Cursor's Grok Bot / the Grok desktop assistant) is a fourth, agent-side transport: use its built-in Grok image tool directly, not illo.py generate, when no user config explicitly selects an engine backend.

Running the engine — set $SKILL_DIR inline in each block. Every engine command below is python3 "$SKILL_DIR/scripts/illo.py" …. Set SKILL_DIR to the absolute path of the directory this SKILL.md was loaded from (it contains scripts/illo.py and assets/) in the same command block that uses it — shell state does not persist between separate command runs, so a value set in an earlier block is gone by the next. If the harness does not expose that path, find the installed scripts/illo.py and use its parent; if neither resolves, stop rather than guessing the working directory. The engine self-locates its own bundled assets, so $SKILL_DIR only has to be right enough to launch illo.py and to point --ref at the bundled character sheet.

Write the block flatten-safe — some hosts (Codex observed) collapse a fenced block to one line, turning a newline into a space. Terminate the assignment with ; (SKILL_DIR="…"; — without it, a flattened SKILL_DIR="…" python3 "$SKILL_DIR/…" becomes an env-prefix whose $SKILL_DIR expands to empty before the assignment applies, so the path collapses to /scripts/illo.py). Put no comment on an assignment or command line (a flattened # comments out the rest of the line and the command silently vanishes), and keep each invocation on one line (a flattened \ continuation injects stray arguments). A wrong or unset value makes doctor (Workflow step 0) fail loudly (can't open file …/scripts/illo.py) — the signal to fix the path, not a skill fault.

• Codex backend (free for Codex subscribers). When the host has a usable Codex CLI — installed, codex login-ed, with the image_generation feature — illo can generate through the user's Codex subscription at no per-image charge (it draws on their Codex quota). No API key, no token: illo only shells out to the user's own CLI. Detected, not assumed; gpt-image-2 is automatic; unsupported on Windows/WSL.
• Grok CLI backend (free for Grok/xAI subscribers). When the host has a usable Grok CLI — installed and grok login-ed — illo can generate through the user's Grok subscription via grok -p (headless), drawing on their Grok quota. Same env-free, token-free subprocess design as Codex. Grok returns JPEG with no alpha, so it cannot make transparent cutouts — those auto-fall back to a cutout-capable backend. The image tool exposes no model selector.
• Grok Bot native transport (agent-side, free for Grok Bot users). When you are Grok Bot — specifically Cursor's Grok Bot / the Grok desktop assistant with the built-in Grok image tool — build the illo prompt and call that tool with the active character's model sheet as a reference image. Do not require the Grok CLI, Codex CLI, or an OpenRouter key; do not treat a missing engine backend as a reason to run init. This is not a generic "host image API" rule and not an illo.py --backend value.
• OpenRouter backend (paid, direct or explicit fallback). Needs an OpenRouter API key in the user's config file — the single credential channel — written once by the user-run init (mode 600). The engine never reads secrets from the environment and never accepts them as command-line arguments. A host without a subscription CLI can select this engine path directly. A failed Codex/Grok CLI render does not spend money automatically: paid fallback requires --allow-paid-fallback. It is model-selectable (--model).

Capsule of the backend/transport model (resolution and precedence, the CLI requirements, the Grok Bot native path, the built-in image tool being automatic, quota vs. charge, cutout limits, Windows/WSL, fallback): read references/backends.md in full before choosing or explaining a backend — the mechanics live there, once.

Setup is the user's job (never enter the key yourself)

Entering an API key is something the user does. Do not type, paste, print, or store the user's key — direct them to bootstrap it:

• Bootstrap (user runs it): python3 "$SKILL_DIR/scripts/illo.py" init — prompts for the key at a hidden prompt (never echoed) and writes the YAML config ${XDG_CONFIG_HOME:-~/.config}/illo/config.yaml (mode 600). It can also store non-secret defaults: --model, --palette, --aspect, --character, --watermark. Use --no-key to update preferences without touching the stored key. (The config is read via PyYAML when installed; without it a minimal built-in parser still reads the flat keys — apiKey, model, … — so generation needs no installs. Only nested settings like watermark need PyYAML: python -m pip install 'PyYAML==6.0.2'.)
• Non-secret prefs may be seeded for the user with the same command and --no-key, but the key itself is theirs to enter.

Hermes Agent only: binary asset repair preflight

Some Hermes versions corrupt binary files (the bundled character sheets) when installing multi-file skills from GitHub — text files survive, binaries don't, and a corrupted sheet silently breaks the character lock. Under Hermes Agent, run this once before first use (and whenever doctor reports assets: CORRUPTED):

bash ${HERMES_SKILL_DIR}/scripts/repair-hermes-assets.sh

It verifies every bundled binary against known-good SHA256 hashes (assets/checksums.txt) and re-downloads only mismatched files from pinned, immutable URLs — a no-op when everything checks out. Under Claude Code, Codex, OpenClaw, or any runtime that installs faithfully: skip this; doctor checks asset integrity everywhere and will say if repair is ever needed.

Read these references as needed

Do not load everything at once. Pull the file that matches the step:

• references/visual-style.md — riso, the house default look: the risograph technique, line language, paper/ink, hard do/don'ts.
• references/styles/<name>.md — the rest of the look library (blueprint, woodcut, pixel, clay, manila, chalk, phosphor, enamel, gouache, felt, diorama, sketchbook, bricks, fizz, bloom, snes), consumed by character packs. Read the active character's style file in full before generating.
• references/character.md — the character rules (the load-bearing test, anti-complexity guardrails, value-follows-palette, the interaction model — declared per pack or derived conservatively from the locked design and reference sheet), the default character Blot, and the custom-pack format. Read before any character work.
• references/character-builder.md — the guided flow for designing and installing a user's own mascot. Read in full before building or replacing a character.
• references/pack-sharing.md — installing characters from the community repo and publishing a pack via PR. Read before any install/publish request.
• references/palettes.md — named presets, default resolution, custom palettes, and the derive-a-palette-from-one-color algorithm. Read in full before choosing or deriving any palette.
• references/composition.md — the two registers (editorial scene / explainer diagram), the diagram-type picker, the explainer's structure types and budget (including labeled stages, arrow notes, and its pack-solve), stagings, turning an idea into a move, the anatomy-action feasibility gate (validate the contact map against the character's interaction model before rendering), the no-recycled-composition rule, and the shot-list format.
• references/cutout.md — the cutout register: transparent compositing assets, contact continuity, pose vocabulary, and generate flags. Read in full before any cutout request.
• references/surprise.md — surprise / random mode: preflight-first, scope parse, random character, provenance variety + three saying candidates (optional parallel verify for sourced modes), interactive picker or --autopick / auto-pick-best, full re-roll on refresh, register after the locked saying, saying bar + sense bar, multi-source quote verification, safety-before-offer, headless contract. Read in full before any surprise/random request.

assets/character-reference.webp is the default character's canonical model sheet — the consistency anchor (used by the engine, below); a custom pack brings its own. Style-calibration examples are not bundled — each style file links its own by URL (fetch when needed): study line density, negative space, and accent restraint. Never copy their compositions — invent a fresh metaphor for the current piece.

Workflow

0. Preflight

Before generating, confirm the engine is ready:

SKILL_DIR="<path to this skill>";
python3 "$SKILL_DIR/scripts/illo.py" doctor

Run the illo.py call standalone — never chained with && — so the displayed exit code is the readiness signal itself (0 = ready): a chained neighbor's failure paints a healthy check as an error.

It reports python, the config path, the resolved model/palette defaults, whether a custom character pack or custom palettes file exists, Codex/Grok CLI detection and the resolved backend/transport, and whether an OpenRouter key is found (without revealing it); exit 0 = the resolved backend is ready. An OpenRouter-only install (no subscription CLI) stays exit 0 — readiness follows the resolved backend, not a hardwired key check (references/backends.md).

Grok Bot native path (agent-side). If you are Grok Bot (Cursor's Grok Bot / the Grok desktop assistant with the built-in Grok image tool) and the user has not explicitly chosen backend: openrouter, backend: codex, or backend: grok, initialize the agent-side transport before relying on doctor:

SKILL_DIR="<path to this skill>";
python3 "$SKILL_DIR/scripts/illo.py" init --backend grok-bot --no-key

Then run doctor normally: exit 0 is meaningful readiness for this path. Missing Codex CLI, Grok CLI, or OpenRouter key are not failures when backend: grok-bot; corrupted assets, unreadable custom packs, malformed palettes, or the wrong SKILL_DIR still fail and must be fixed before rendering. Generate in Step 5 by calling Grok Bot's built-in Grok image tool with the active model sheet reference. This route is only for Grok Bot's own Grok image tool; other agents with unrelated image tools must use the engine backends below.

Short path for Grok Bot: run init --backend grok-bot --no-key once when backend is unset/auto, run doctor for assets/config/packs, use packs commands normally (including packs install --all after install so community characters are local), read the same references, build the same prompt, then call Grok Bot's built-in Grok image tool with the active character reference. Skip illo.py init for OpenRouter unless the user explicitly wants OpenRouter or another engine backend default, and skip illo.py generate unless the user explicitly selected an engine backend.

After the first successful Grok Bot install and bulk character install, ask once whether the user wants periodic checks for skill updates (npx skills update) and character updates (packs update). Default is off: if they say no, do not answer, or the host has no recurring-job mechanism, set up nothing. Only create a recurring check/reminder on an explicit yes, and never silently update — surface the proposed skill/character update and get consent before applying it.

Config migration — surface the backend choice interactively. When you are going to use illo.py generate, if doctor reports backend: NEEDS CHOICE (or generate hard-stops saying the config "is out of date"), this user's config predates the backend choice — they have an older install and have never been offered a subscription CLI. Do not pick for them silently. Surface an interactive choice using the platform's blocking-question capability (AskUserQuestion in Claude Code, the equivalent elsewhere; where the host has none — e.g. a plain chat session — ask the same one choice as a concise message and wait for the reply, never picking silently): "illo now has image backends/transports — which would you like?" with four options — Codex (free, your Codex subscription), Grok CLI (free, your Grok subscription; no transparent cutouts), Grok Bot (agent-side native tool; use only when you are Grok Bot), and OpenRouter (pick the model: Grok Imagine, Nano Banana, GPT Image, and others). Persist the answer without touching any existing key: python3 "$SKILL_DIR/scripts/illo.py" init --backend <codex|grok|grok-bot|openrouter> --no-key, then continue. A brand-new install (no config at all) is ordinary onboarding, not this migration — it does not fire.

Prefer your own CLI when you are a subscription-CLI agent. The engine's auto-default reads host capability (Codex > Grok > OpenRouter; it can't tell which agent invoked it) — but you know which agent you are. So when you are a subscription-CLI agent and your own CLI is usable on this host, add your own backend flag to generate for non-cutout renders: the Grok CLI agent adds --backend grok, the Codex agent adds --backend codex. This keeps "in Grok CLI, generate with Grok" true even on a host that also has Codex, with no runtime-sniffing in the engine. Cutouts ignore this (Grok can't make them — they auto-fall back). A user's config backend: overrides everything. Resolution and precedence mechanics: references/backends.md.

For Grok Bot, the equivalent self-identify rule happens before generate: when backend is unset/auto, persist backend: grok-bot with init --backend grok-bot --no-key and use the native Grok image tool path above. If the user explicitly configured or requested an engine backend, honor that choice instead of silently switching to Grok Bot native.

Read the printed config path before concluding the key is missing: under Hermes, multi-profile setups can resolve HOME/XDG_CONFIG_HOME to another profile's home (e.g. …/profiles/<name>/home/.config/illo/…), so a key that exists looks absent. If the path points at the wrong profile, re-run with the right HERMES_HOME/HOME/XDG_CONFIG_HOME rather than treating the key as missing. If the key is genuinely missing, stop and ask the user to run python3 "$SKILL_DIR/scripts/illo.py" init themselves — do not enter the key for them. In a chat session the user can't run commands where they are, so shrink their host-side step first: run init --no-key yourself (allowed — it scaffolds the config with defaults and a commented # apiKey: placeholder, mode 600, never touching a key), then offer the user two equivalent one-time options on the machine the agent runs on (that host is theirs — it's where they installed the agent): run python3 <resolved absolute $SKILL_DIR>/scripts/illo.py init (hidden prompt), or open ~/.config/illo/config.yaml and fill in the apiKey: line. The key must never transit the chat: never ask for it in a message, and if the user pastes it anyway, do not use it — tell them to revoke that key at openrouter.ai and set a fresh one on the host (the pasted key now lives in chat history and platform servers). Never copy a key from the environment or any other store into the config yourself — the user is the only writer of that line — with one scoped exception: an ephemeral cloud workspace (Claude Code web, Codex cloud, CI) where the user provisioned OPENROUTER_API_KEY through the platform's secrets mechanism. That provisioning is itself the user's deliberate, workspace-scoped consent, and there is no interactive prompt or persistent home for init — so there, seed the config from the workspace secret once (the "Cloud & CI" one-liner in README.md). On a personal machine an ambient env var proves nothing about intent (it may belong to other tools) — the rule stands: never copy it.

Optional pack-freshness offer (preflight, consent-first). When this run will render with an installed community pack (doctor lists packs; installs carry a .version stamp), optionally check freshness: python3 "$SKILL_DIR/scripts/illo.py" packs list flags stale installs ([installed 1.0.0 — 1.0.2 available]). The check may run here, but the offer fires once the active pack is known — after Step 2 resolves the character (or after surprise mode's character roll), immediately before the first render that uses it. If that resolved pack is stale, offer once — via the platform's blocking-question capability, as in the config migration above — to refresh it before rendering, and run packs update <name> only on an explicit yes (updating overwrites the local copy; the hand-edit warning and --as alternative are in references/pack-sharing.md). Never update silently, and never block on this: a "no", an offline host, a registry error, or a headless/scheduler run (e.g. surprise --autopick) all continue with the pinned copy — a pack without a declared ## Interaction model still plans safely via the conservative derivation (references/character.md). Skip the check entirely when no community-installed pack is involved.

1. Read the input — and clarify a thin concept (briefly)

Three kinds of input, handled differently:

• Surprise / random ("surprise me", "random", "surprise me with art quote using bray", "surprise me --autopick", and close variants) — the ask is invent-and-render, not a supplied thesis. Stop and read references/surprise.md in full, run Step 0 first, then resolve character and provenance there (ignore defaultCharacter; random character when unnamed), build three saying candidates and lock one via picker or auto-pick-best, pick register from the locked saying, then continue Steps 3–7 as one image — Steps 0 and 2 are skipped in that render pass because preflight and pack are already done. Do not enter the thin-concept Q&A path below. A prompt that already names a concrete idea ("illustrate 'you are the bottleneck'") is not surprise mode even if it also says "surprise me".

• A URL / article / paste / long post carries its own context — but never generate from the first vivid detail. Route it first (references/composition.md, "Source routing"): classify the source's shape and genre, infer the requested artifact's job (what this image must do for its audience), separate that job from the source's most drawable mechanism, lock the main thesis in one sentence (a hero locks the source/artifact job, not its loudest evidence — the genre guardrails say what each genre heroes), then pick the coverage — hero, hero + per-section set (the full article job), set, mini-comic, or shot list first. Sets need placements: compact sources (a tweet, one concept) never yield a set — their multi-beat form is the mini-comic. Pull the load-bearing moments — the few places that turn on a judgment, a loop, an input→output, a before/after, or a trap — never one image per paragraph. The text already says what it's about, so don't interrogate the user, with one exception: a materially multi-beat source (long article, postmortem, multi-claim launch) gets a single coverage question before any multi-image spend — unless the user already named the coverage. A lone image from a multi-beat source is a hero, delivered saying so — not as coverage of the piece.

• A bare concept or one-liner (e.g. "illustrate 'you are the bottleneck'") usually underspecifies the picture. Ask up to ~3 quick questions — only the ones that change the output — then build. Draw from:

  • the single takeaway (what should the reader conclude?),
  • where it's headed (blog / deck / X post / X article body / X Article banner → sets palette, aspect, pixel normalization, and watermark),
  • the shape: one image (the default), a mini-comic (2–4 panels in one image — only when the idea itself advances through stages), or several separate images — plus any must-include element or constraint. The shape follows the idea, never the destination ().

2. Resolve the character

Surprise / random mode: skip this step — character was already resolved in references/surprise.md (named pack, or random among installed + Blot; never defaultCharacter). Continue at Step 3+.

Installed packs live under ${XDG_CONFIG_HOME:-~/.config}/illo/characters/ (format and location details: references/character.md); doctor lists what's installed. A user can keep several and pick per run. First match wins:

1. Explicit request — "use ", "as ": that pack (or the shipped default when asked for by name, blot). When the word matches no pack name, resolve by approximation: match it against each installed pack's Aliases: line and subject (the character.md opening line and Locked design Body) — doctor prints names + aliases, so this needs no file reads in the common case — and against catalog descriptions (packs list). So "use ox" finds a pack subtitled an ox (e.g. yoke). On one clear match, use it and name it; on several, ask which; on none, say so before falling through.
2. Config default — defaultCharacter from the user config, if set.
3. Shipped default — Blot (spec in references/character.md, model sheet assets/character-reference.webp).

Once resolved, read the pack's character.md and use its prompt spec, value rules, optional Cutout chroma: compatibility preference, and reference.png everywhere the default's would be used.

When rerouting an article set to a new character — especially after a weak attempt, or for a technical/platform essay — read references/article-set-character-reroute.md in full before planning or rendering. Do the legibility preflight there before spending renders.

If the user wants a new character, that is the character builder (references/character-builder.md); if they want someone else's, packs install from the community repo (references/pack-sharing.md). Either way, install first, then continue here.

3. Plan (shot list) — when asked to plan, or for anything multi-image

If the user wants planning ("where should this be illustrated", "shot list"), output a shot list before generating. Per image: placement, the one idea, the artifact job, the register (editorial unless the row passes the explainer gate), the staging (or structure type — pick per references/composition.md, "Pick the diagram type"), what the mascot is doing, the palette, and the text hierarchy — primary read/title when the artifact needs one, plus short supporting labels/callouts within the per-register budgets in references/composition.md. Let the anchor count drive how many (bands and the never-pad rule are in references/composition.md). When a stretch of the piece advances through stages in one place, plan a single mini-comic image there instead of several — the mini-comic-vs-separate routing is in references/composition.md.

For article-set character reroutes, add the mandatory preflight fields from references/article-set-character-reroute.md before any render: section claim, visual object/action, and reader mapping. Reject rows that need a private metaphor glossary or more than one conceptual substitution.

4. Resolve the palette (the style is the character's)

Style is not separately resolvable: the active character's pack carries it — the Style: line in its character.md names a bundled look (references/styles/<name>.md, riso in visual-style.md) or a custom one at ${XDG_CONFIG_HOME:-~/.config}/illo/styles/<name>.md; absent line = riso. Blot is riso. For any non-riso style, read its file in full: it supplies the STYLE and LINE LANGUAGE prompt blocks, the palette mapping, the character treatment, and extra QA checks. A request for the same character in a different look is a variant-pack build (route table) — never restyle on the fly.

Palette: read references/palettes.md in full and resolve there — it holds the resolution order (explicit request, then destination cue via the user's palettes file, then config default, then house ink-punch), the named presets, custom palettes, and the derive-a-palette-from-one-color algorithm. End with concrete hex values; when the pack's style isn't riso, run them through that style's palette mapping.

5. Generate — reference-locked, one metaphor per image

Cutout branch. When the request routed to the cutout register, read references/cutout.md in full first — it covers backend-aware transparency (Codex native alpha by default; chroma compatibility for OpenRouter or explicit --chroma), registration-locked silhouette (no ink-layer offset), --cutout /--aspect 1:1, OpenRouter --image-config, and manifest cutout_alpha disclosure. Build the prompt from references/prompt-recipe.md, "Cutout variant" — not the editorial template — and omit manual BACKGROUND: / output-format instructions; the engine appends the contract for the backend that actually runs. Pass --chroma only to force a compatibility reroll. Use only the character model sheet as --ref (no editorial style anchor, no watermark). QA against the cutout section of references/quality-bar.md. Skip the editorial shot-list / thesis steps.

Editorial and explainer. When the locked type is labeled stages, run the pack-solve scratch in references/composition.md ("Labeled stages — skeleton, then pack-solve") before writing the prompt — stage list → operator stage → contact map → bind; do not invent a look. Build a full prompt per image from references/prompt-recipe.md (scene + structure + communication hierarchy + style + the active character's spec + resolved palette hexes + the per-register text budget), write it to a file, and render it. Pass the active character's model sheet as --ref every time — that reference conditioning is what keeps the mascot on-model; style and palette come from the prompt, so both stays swappable. A pack's sheet is born in its own style, so sheet and style always match — no cross-style reference juggling. (Under Hermes Agent, the asset-repair preflight above must have run before the first --ref use — a corrupted sheet conditions every render on garbage.)

Grok Bot native render. If you are Grok Bot and the native path from Step 0 applies, do not run illo.py generate. Use the same full prompt recipe, same aspect ratio, same character lock, same style-anchor rule for sets, and call Grok Bot's built-in Grok image tool. Attach the active character's model sheet as a reference image (assets/character-reference.webp for Blot, or the pack's reference.png); for later images in a set, also attach the accepted style anchor image. Ask the tool to save/return the generated file and treat that saved path as the engine JSON .path equivalent for QA and delivery. Grok Bot's image tool is the same Grok image-model class as the Grok CLI transport: no model selector, no OpenRouter billing, and no alpha channel. Transparent cutouts stay off this path; route them to a cutout-capable engine backend instead, or stop and ask for that backend to be configured.

Set SKILL_DIR inline (see Prerequisites), and use the bundled sheet as REF — or the active pack's reference.png for a custom character. Add --model <id> to override the config/default model for this image (OpenRouter backend only):

SKILL_DIR="<path to this skill>";
REF="$SKILL_DIR/assets/character-reference.webp";
python3 "$SKILL_DIR/scripts/illo.py" generate --prompt-file /tmp/shot-01.txt --ref "$REF" --aspect 16:9 --out "assets/<slug>-illustrations/01-topic.png"

For engine renders, illo.py generate prints a JSON line per image ({path, backend, model, id, cost, width, height, label, prompt}; backend is codex, grok, or openrouter, and model/id/cost are OpenRouter-only — they are null on a CLI-served record (Codex or Grok). cost is null unless --cost is passed — gallery backfills it) and appends the same record to <out-dir>/manifest.jsonl. Read .path — it may differ from --out: the engine names the file by the actual encoding (some models return JPEG bytes, so a requested .png lands as .jpg). Use .width/.height to catch a square when 16:9 was requested (re-roll). A failed Codex/Grok CLI render stops by default even when an OpenRouter key is configured. Add --allow-paid-fallback only when the user has explicitly approved a pay-per-image retry. Direct --backend openrouter renders and the intentional Grok-cutout redirect remain direct routes and do not need this flag. Generate each image separately — never combine ideas into one canvas. Default aspect is 16:9; use 1:1 for square social, 9:16/4:5 for vertical, and 1536:640 for an X Article banner / hero. For X Article banners, the platform target is 1536 × 640 px. Generate through the normal image pipeline; do not manually composite or rebuild the scene from crops as a substitute for an illo render. Check .width/.height, and only do final post-processing when it is a non-distorting resize/crop that preserves normal proportions and all essential information. Never stretch or squash the art to force exact dimensions. Pass --label for a caption that shows in the gallery.

Sets read as one artist. For any multi-image set, the first image that passes the full quality bar (and, for a hero in a rerouted article set, passes the thesis-legibility gate in references/article-set-character-reroute.md; never anchor on an unvetted render — a failed anchor, e.g. an off-palette ground or illegible metaphor, would propagate its failure set-wide) becomes the set's style anchor: pass it as a second --ref after the character sheet for every later image in the set and for every re-roll of a set member, so line weight, halftone density, and flat-vs-dimensional treatment stay consistent throughout. The same trick locks style for a one-off: add any finished example as a second --ref.

Model choice (OpenRouter backend only). --model and config model: are an OpenRouter-only axis — on Codex, Grok CLI, and Grok Bot native the image model is automatic and --model does not apply (references/backends.md). For the OpenRouter path, read references/models.md in full before passing any --model (or whenever the user names a model in plain language or asks for "best quality" / "cheapest"): it holds the friendly-name → OpenRouter id map, per-model traits, the aspect-ratio caveat, and the 404/fallback handling. Resolution is --model > config model > built-in default.

Watermark / attribution (optional, off by default). The skill ships with no default watermark — the text comes only from the user's watermark config map (read from the config file) or an explicit request, so installers never inherit someone else's handle. The resolution order, the prompt line to append, and the two-render caveat are in references/prompt-recipe.md.

5b. Batches & comparison (only when it helps)

Default to ONE image. Fan out only when the user asks for options/comparison or the piece is important enough to be worth it — and say first what each image costs: on the Codex backend it draws on the user's Codex quota (no per-image charge), on Grok CLI or Grok Bot native it draws on the user's Grok quota, and on the OpenRouter backend it bills their OpenRouter account (typically under ten cents per image, varying by model). Keep N small (2–4). Orchestrate the loop with the engine's primitives:

newrun prints a fresh run dir (/tmp/illo/<runid>) into RUN. Record the user's VERBATIM request (URL, pasted text, concept) to request.txt — the gallery shows it as provenance so anyone can tell what the run was for. Adapt each generate line below to a real path and run it on its own:

SKILL_DIR="<path to this skill>";
RUN=$(python3 "$SKILL_DIR/scripts/illo.py" newrun);
printf '%s' "<the verbatim request>" > "$RUN/request.txt"
# (a) VARIATIONS — same prompt+model, pick-the-best:
python3 .../illo.py generate --prompt-file p.txt --ref <ref> --count 4 --label "draft→ship" --out "$RUN/v.png"
# (b) MODEL COMPARISON — loop the SAME prompt over the chosen models
#     (full OpenRouter ids from references/models.md):
for m in <model-id-1> <model-id-2>; do
  python3 .../illo.py generate --prompt-file p.txt --ref <ref> --model "$m" --label "$m" --out "$RUN/$(basename $m).png"; done
# (c) CONCEPT VARIATIONS — different prompts (different stagings) for one idea:
python3 .../illo.py generate --prompt-file staging-A.txt --ref <ref> --label "as a funnel" --out "$RUN/a.png"
python3 .../illo.py generate --prompt-file staging-B.txt --ref <ref> --label "as a crossing" --out "$RUN/b.png"

python3 "$SKILL_DIR/scripts/illo.py" gallery "$RUN" --title "<the piece or request>" --open
# always pass --title so a saved gallery stays identifiable later;
# add --embed for a single portable file (images inlined)

Every generate self-records to $RUN/manifest.jsonl; gallery assembles them into one page with each image's label, model, dimensions, cost, and a collapsible prompt — the prompt toggle is what makes concept-variation comparison readable (the prompt is the variable). Always present the gallery with a recommendation, not a raw dump — and in a chat session, present the labeled candidates directly in the chat instead of a gallery (delivery routing in step 7). Multi-model failures are per-image (an unavailable model errors that one render only); keep the rest.

6. QA and iterate

Check every image against references/quality-bar.md. Re-roll or edit when the mascot is decorative or off its locked spec, the body is wrong-value for the palette, label text sits on a colored fill, the accent has spread past the character's accent part + 1–2 elements, an unwanted title bar appears, the composition copies an example, or text is misspelled. Subject scale varies run-to-run — re-roll if the subject is tiny (check .width/.height in the JSON: a square back when 16:9 was requested → re-roll). When a re-roll supersedes a render, rebuild any delivery gallery with --exclude <superseded label> (repeatable) so rejected rolls don't appear in the review artifact.

7. Deliver — match the session's medium

Copy finals next to the user's work when appropriate; never overwrite existing assets without being asked. Filenames carry the role — they are the only metadata that survives a document attachment, so make them self-identifying: 00-hero-<slug>.png for the hero, then 01-<section-slug>.png, 02-<section-slug>.png, … for anchors in piece order (assets/<slug>-illustrations/). Then report: how many images, the palette used, which are strongest vs optional — and for any multi-image job, a placement map: one line per image naming the file, its role (hero, or after which section), and the one idea it lands, so the user can drop each file where it belongs without re-deriving the plan. Deliver the images themselves the way this session can actually show them:

• Filesystem sessions (IDE/terminal agents — Claude Code, Codex, Cursor): report each final's absolute path (the engine's JSON .path is already absolute) and present the gallery for multi-image runs. The file on disk already is the original — never emit [[as_document]] here: it's a Hermes gateway token, literal noise in any other runtime. If the runtime has its own in-chat file delivery, use that.

• Grok Bot native sessions: deliver the file returned by Grok Bot's built-in image tool inline/as an attachment in chat, and include its saved file path in the same role that engine renders use .path. The returned file is the original for this transport; do not ask the user to configure OpenRouter just to retrieve it.

• Chat sessions (the user is on a messaging surface — Hermes over Telegram/Discord/WhatsApp, or any chat surface with lossy media delivery — and cannot open local files): a path alone is not a complete deliverable; the image must land in the chat, and a final must arrive as the original file. Platform photo delivery recompresses images — exactly what destroys riso grain, halftone texture, ink-layer offset, and fine hand-lettering — so finals are delivered as document attachments. On Hermes, tag each final with an explicit MEDIA: attachment tag — the tag is MEDIA: immediately followed by the absolute path, no space — and the literal directive [[as_document]] in the same reply. Do not rely on a bare absolute path for a final: bare paths can pass through to the user as literal text instead of being dispatched as an attachment.

  MEDIA:/absolute/path/to/final.jpg
  [[as_document]]
  

  Candidate/options rounds may use normal inline photo delivery when quick glances help — say so ("preview — original file to follow") — but a final is never delivered that way. Skip the HTML gallery in chat — the user has no easy way to open or host it; send the labeled finals directly with the recommendation as text, and only build gallery --embed (one self-contained file) if a portable artifact is explicitly requested, delivering it with [[as_document]].

Before the final reply in a chat session, check:

• every final's path came from the engine's JSON .path, not the requested --out (the actual extension may differ);
• every final appears as an explicit MEDIA:/absolute/path attachment tag in the reply;
• [[as_document]] is in the reply unless this is explicitly preview-only;
• rejected/re-rolled candidates are excluded from delivery;
• the text says what was made — character, palette, strongest final, and for sets the placement map (which file is the hero, which follows which section) — without implementation noise.

Output discipline

Pre-generation planning is short and concrete. Post-generation, let the images speak — report what was made and where, not style theory. Keep labels few and short; the fewer words baked into an image, the more reliably it renders.

Talk like a person doing the work, not a recap of this file. Never narrate workflow steps or jargon in chat: doctor, preflight, provenance, register, saying bar, thesis, backend, or "doctor's green." Status, if any, is ordinary speech, not a liturgy of steps. When surprise mode picks an unnamed character, introduce the character once in plain English — pack name plus what they are ("Inch, the chalk inchworm") — then show the lines and ask which one. Never status-ping with the name alone ("Inch."), say "Still Inch," or ask "which one should draw?" The user hears the result — character, sayings / image, what was made — not the procedure.