feat: contributor graph PNG generator + API endpoint

matplotlib chart with dual axes — cumulative claims (#00d4aa) and
contributors (#7c3aed) on dark background. 1200x630 for Twitter.
Auto-regenerates hourly via /api/contributor-graph endpoint.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

scripts/contributor-graph.py

@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+"""Generate cumulative contributor + claims PNG for Twitter embedding."""
+
+import json
+import subprocess
+import sys
+from datetime import datetime, timedelta
+from pathlib import Path
+
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+from matplotlib.ticker import MaxNLocator
+
+ACCENT = "#00d4aa"
+PURPLE = "#7c3aed"
+BG = "#0a0a0a"
+TEXT = "#e0e0e0"
+SUBTLE = "#555555"
+OUTPUT = Path("/opt/teleo-eval/static/contributor-graph.png")
+
+
+def get_data():
+    """Fetch from local API."""
+    import urllib.request
+    with urllib.request.urlopen("http://localhost:8081/api/contributor-growth") as r:
+        return json.loads(r.read())
+
+
+def build_continuous_series(milestones, start_date, end_date):
+    """Expand milestone-only contributor data into daily series."""
+    dates = []
+    values = []
+    current = 0
+    milestone_map = {}
+    for m in milestones:
+        d = datetime.strptime(m["date"], "%Y-%m-%d").date()
+        milestone_map[d] = m["cumulative"]
+
+    d = start_date
+    while d <= end_date:
+        if d in milestone_map:
+            current = milestone_map[d]
+        dates.append(d)
+        values.append(current)
+        d += timedelta(days=1)
+    return dates, values
+
+
+def render(data, output_path):
+    fig, ax1 = plt.subplots(figsize=(12, 6.3), dpi=100)
+    fig.patch.set_facecolor(BG)
+    ax1.set_facecolor(BG)
+
+    claims = data["cumulative_claims"]
+    contribs = data["cumulative_contributors"]
+
+    claim_dates = [datetime.strptime(c["date"], "%Y-%m-%d").date() for c in claims]
+    claim_values = [c["cumulative"] for c in claims]
+
+    start = min(claim_dates)
+    end = max(claim_dates)
+
+    contrib_dates, contrib_values = build_continuous_series(contribs, start, end)
+
+    # Claims line (left y-axis)
+    ax1.fill_between(claim_dates, claim_values, alpha=0.15, color=ACCENT)
+    ax1.plot(claim_dates, claim_values, color=ACCENT, linewidth=2.5, label="Claims")
+    ax1.set_ylabel("Claims", color=ACCENT, fontsize=12, fontweight="bold")
+    ax1.tick_params(axis="y", colors=ACCENT, labelsize=10)
+    ax1.set_ylim(bottom=0)
+
+    # Contributors line (right y-axis)
+    ax2 = ax1.twinx()
+    ax2.set_facecolor("none")
+    ax2.fill_between(contrib_dates, contrib_values, alpha=0.1, color=PURPLE, step="post")
+    ax2.step(contrib_dates, contrib_values, color=PURPLE, linewidth=2.5,
+             where="post", label="Contributors")
+    ax2.set_ylabel("Contributors", color=PURPLE, fontsize=12, fontweight="bold")
+    ax2.tick_params(axis="y", colors=PURPLE, labelsize=10)
+    ax2.yaxis.set_major_locator(MaxNLocator(integer=True))
+    ax2.set_ylim(bottom=0, top=max(contrib_values) * 1.8)
+
+    # Annotate contributor milestones with staggered offsets to avoid overlap
+    offsets = {}
+    for i, m in enumerate(contribs):
+        d = datetime.strptime(m["date"], "%Y-%m-%d").date()
+        val = m["cumulative"]
+        names = [n["name"] for n in m["new"]]
+        if len(names) <= 2:
+            label = ", ".join(names)
+        else:
+            label = f"+{len(names)}"
+        y_off = 8 + (i % 2) * 14
+        ax2.annotate(label, (d, val),
+                     textcoords="offset points", xytext=(5, y_off),
+                     fontsize=7, color=PURPLE, alpha=0.8)
+
+    # Hero stats
+    total_claims = data["summary"]["total_claims"]
+    total_contribs = data["summary"]["total_contributors"]
+    days = data["summary"]["days_active"]
+    fig.text(0.14, 0.88, f"{total_claims:,} claims", fontsize=22,
+             color=ACCENT, fontweight="bold", ha="left")
+    fig.text(0.14, 0.82, f"{total_contribs} contributors · {days} days",
+             fontsize=13, color=TEXT, ha="left", alpha=0.7)
+
+    # X-axis
+    ax1.xaxis.set_major_formatter(mdates.DateFormatter("%b %d"))
+    ax1.xaxis.set_major_locator(mdates.WeekdayLocator(interval=2))
+    ax1.tick_params(axis="x", colors=SUBTLE, labelsize=9, rotation=0)
+
+    # Remove spines
+    for ax in [ax1, ax2]:
+        for spine in ax.spines.values():
+            spine.set_visible(False)
+
+    # Subtle grid on claims axis only
+    ax1.grid(axis="y", color=SUBTLE, alpha=0.2, linewidth=0.5)
+    ax1.set_axisbelow(True)
+
+    # Branding
+    fig.text(0.98, 0.02, "livingip.xyz", fontsize=9, color=SUBTLE,
+             ha="right", style="italic")
+
+    plt.tight_layout(rect=[0, 0.03, 1, 0.78])
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    fig.savefig(output_path, facecolor=BG, bbox_inches="tight", pad_inches=0.3)
+    plt.close(fig)
+    print(f"Saved to {output_path} ({output_path.stat().st_size:,} bytes)")
+
+
+if __name__ == "__main__":
+    out = Path(sys.argv[1]) if len(sys.argv) > 1 else OUTPUT
+    data = get_data()
+    render(data, out)