figure-spec

Files (2)

• SKILL.md
• figure_renderer.py · scripts/

SKILL.md (first lines)

# FigureSpec: Deterministic JSON → SVG Figure Generation

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md):
> resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP)
> with `reviewer_route.py` through the canonical helper resolver, preserving this
> slot's tier, fresh contexts, source/image inputs and deterministic gates.
> Codex examples/pins below apply only to `backend=codex`; other routes use their
> own first-call/reply contract. Save the route and actual returned identity;
> unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual
> families/completion/scope. Forward invocation reviewer/model/effort overrides
> to reviewer-bearing children. Generation workers are unchanged.


Generate publication-quality **architecture diagrams**, **workflow pipelines**, **audit cascades**, and **system topology** figures as editable SVG vector graphics using a deterministic JSON → SVG renderer.

## When to Use This Skill

**Use `figure-spec`** for:
- System architecture diagrams (layered, hub-and-spoke, multi-plane)
- Workflow / pipeline figures
- Audit cascade / flow-control diagrams
- Any structured diagram where node positions, connections, and groupings are semantically important
- Figures that need to be edited/tweaked later (SVG is plain text)
- Figures where determinism matters (same spec → same SVG)

**Do NOT use for:**
- Data plots (bar/line/scatter) — use `/paper-figure`
- Natural/qualitative illustrations — use `/paper-illustration`
- Quick state-machine / flowchart — use `/mermaid-diagram` (lighter syntax)

## Core Properties

- **Deterministic**: identical FigureSpec JSON always produces identical SVG output (for a fixed renderer version + fonts)
- **Editable**: SVG output is plain-text, can be post-edited by hand or programmatically
- **Validated**: renderer enforces schema, rejects malformed specs with clear error messages
- **Shape-aware**: edge clipping works correctly for rect/rounded/circle/ellipse/diamond
- **CJK support**: multi-line labels with proper Chinese character width estimation
- **No external API**: runs fully local, no network, no API keys

## Tool Location

Phase 3.1 (Arch C) move: the canonical implementation now lives at
`skills/figure-spec/scripts/figure_renderer.py` (this SKILL's own
`scripts/` subdirectory). A backwards-compatible shim at
`tools/figure_renderer.py` forwards to the canonical file via
`os.execv`, so existing users with `.aris/tools/figure_renderer.py`
or a manually copied `tools/figure_renderer.py` keep working
unchanged.

Resolve `$FIGURE_RENDERER` with the hybrid chain (layer 0 prefers the
self-contained location for the owning SKILL; layers 1-4 are the
shared-runtime chain documented in
[`shared-references/integration-contract.md`](../shared-references/integration-contract.md) §2,
Policy A — skill-local gate):

```bash
# Layer 0: self-contained (CC 1.0+ exposes $CLAUDE_SKILL_DIR).
FIGURE_RENDERER=""
if [ -n "${CLAUDE_SKILL_DIR:-}" ] && [ -f "$CLAUDE_SKILL_DIR/scripts/figure_renderer.py" ]; then
  FIGURE_RENDERER="$CLAUDE_SKILL_DIR/scripts/figure_renderer.py"
fi
# Layers 1-4: shared-runtime chain (legacy compatibility + non-CC hosts).
if [ -z "$FIGURE_RENDERER" ]; then
  cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
  if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills.txt ]; then
      ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true
  fi
  if [ -z "${ARIS_REPO:-}" ] && [ -f "$HOME/.aris/repo" ]; then
      ARIS_REPO=$(cat "$HOME/.aris/repo" 2>/dev/null) || true
  fi
  FIGURE_RENDERER=".aris/tools/figure_renderer.py"
  [ -f "$FIGURE_RENDERER" ] || FIGURE_RENDERER="tools/figure_renderer.py"
  [ -f "$FIGURE_RENDERER" ] || { [ -n "${ARIS_REPO:-}" ] && FIGURE_RENDERER="$ARIS_REPO/tools/figure_renderer.py"; }
  [ -f "$FIGURE_RENDERER" ] || FIGURE_RENDERER=""
fi
[ -z "$FIGURE_RENDERER" ] && {
  echo "ERROR: figure_renderer.py not resolved (layer 0: \$CLAUDE_SKILL_DIR/scripts/; layers 1-4: .aris/tools/, tools/, \$ARIS_REPO/tools/, \$ARIS_REPO/tools/ via ~/.aris/repo)." >&2
  echo "       /figure-spec cannot produce SVG output. Fix: rerun bash tools/install_aris.sh or smart_update.sh (refreshes ~/.aris/repo), or copy the helper from \$ARIS_REPO/skills/figure-spec/scripts/." >&2
  exit 1
}
```

Invoke:

```bash
python3 "$FIGURE_RENDERER" render <spec.json> --output <out.svg>
python3 "$FIGURE_RENDERER" validate <spec.json>
python3 "$FIGURE_RENDERER" schema
```

## Workflow

### Step 1: Understand the Diagram Goal

From `$ARGUMENTS` (description or path to `PAPER_PLAN.md` / `NARRATIVE_REPORT.md`), identify:
- **Purpose**: architecture, workflow, pipeline, audit cascade, topology?
- **Main entities**: what are the boxes?
- **Relationships**: how do they connect? (uses, produces, calls, verifies, chains)
- **Grouping**: do entities cluster into named regions?
- **Hierarchy vs network**: stacked layers, left-to-right flow, or central hub?

### Step 2: Draft the FigureSpec JSON

Canvas sizing guide:
- Single-column figure: ~500×350 px
- Two-column (full-width): ~900×500 px
- Tall topology: ~700×700 px

Start from a template based on the diagram type:

**Architecture (stacked rows)**:
```json
{
  "canvas": {"width": 900, "height": 520},
  "nodes": [
    {"id": "layer1_label", "label": "Layer 1", "x": 450, "y": 60, ...},
    {"id": "node_a", "label": "A", "x": 180, "y": 120, ...},
    {"id": "node_b", "label": "B", "x": 350, "y": 120, ...}
  ],

From wanshuiyin/Auto-claude-code-research-in-sleep, MIT.

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