The 53 Report is live. Full tech stack: SQLite, MCP server, Claude Code agentic workflow for the editorial pipeline, Astro 5, Docker on a Hetzner VPS. Here is how it all connects.
The data layer is the SQLite database from post 045. Every draft pick since 1980, weekly rosters since 2002, per-game snap counts since 2012. About 1.3 million rows. A pick counts as a hit if the player produced 500 or more snaps in any single regular season, the line where they spent at least one year as a real rotational contributor (we started at 100 snaps and tightened the bar after publishing the first three articles).
On top of that sits an MCP server running in Docker on nix1 over Tailscale. Eight tools: team draft hit rate, round hit rate, round trends heatmap, roster composition, pick outcome for a single selection, player career arc, player search, and a database health check. The server runs SSE at port 3711 and gets queried by Claude Code during every editorial run.
The editorial pipeline is where it gets interesting. Four stages: Scout, Beat, Editor, Coach. All running inside Claude Code as custom skill agents.
Scout is read-only. It hits the MCP and returns a structured evidence pack with three to five ranked angles. No prose, no opinions, just numbers and angle proposals, ranked by anomaly vs. league, anomaly within team, regime shift signals, single-pick stories, and counter-narratives.
Beat takes the evidence pack plus the approved angle and writes the article. Every number has to be traceable to Scout's pack or a clean derivation from it. No new numbers, no player names Scout didn't surface. Targets 1,800-2,600 words depending on shape, with narrative and data woven together in every section.
Editor is the stat-fidelity gate. It reads Beat's draft against Scout's pack and returns PASS, REVISE, or BLOCK. A hallucinated stat is an automatic BLOCK. No league rank gets through without the raw value, population denominator, and era window in the same sentence.
Coach orchestrates the whole run. It reads the publishing calendar, picks the next queued team, spawns Scout, presents angles, hands the approved one to Beat, runs Editor, and calls the deploy script only after explicit approval. Never ships without that sign-off.
The product is GM Performance Grading: how well NFL general managers draft and retain talent. Three article shapes: scorecard (tenured GM, four graded columns, final letter grade), narrative (paradox or anomaly, no grade), and methodology (league-wide framing, no team focus). Three published pieces so far, twenty-nine teams queued.
The site is Astro 5, static build, deployed via rsync to Zion (Hetzner VPS, Plesk-managed). DNS through Cloudflare, proxied, Full Strict SSL. Build is clean in under ten seconds.
Long-term target is a paper for SSAC 2027 (abstract due around October 2026) and a staff or contributor role at an NFL team analytics group or a shop like SumerSports or The 33rd Team. The dataset edge is the window: Dubow's AP piece used a 2021-2024 window with binary roster data. SIS used first-round picks only with a four-year endpoint. This stack goes multi-year, snap-weighted, and position-weighted across every round.
Next up: interactive analysis with logins and custom date range filters. After that, a longer story-driven piece on the BNM blog, less technical, more about how this came together.