Task halted — insufficient data for a credible analysis

2026-04-21 · Chess Research

Topic requested: Most common blunders by Black in the Smith-Morra Gambit under 1200 Chess.com rating, in Bullet chess.

Why I am stopping rather than producing the article

Per the project rules I attempted to source all data through the grandmaster-guide MCP. The relevant findings:

Check	Result
`opening-deep-stats` for ECO B21 (Smith-Morra)	Total 8,078 games across all ratings/time controls
Smith-Morra games tagged as Bullet in the dataset (all ratings)	315 games total
Smith-Morra Bullet games in the 700-900 + 900-1100 Lichess bands (≈ Chess.com 500-900)	A small fraction of those 315 — the dataset's bullet break-down is not split by rating band, but the per-band totals (528 + 875) are dominated by blitz and rapid
`lichess-games` endpoint filtering	Does not support ECO/opening or time-class filters; ECO must be filtered client-side
Random sample of 100 sub-1500 games via `lichess-games`	0 Smith-Morra games found (B21 is rare; it appears in roughly 0.1-0.3% of sub-1500 games)
Lichess public Opening Explorer (fallback)	Returns HTTP 401 Unauthorized from this sandbox, so it cannot be used as a substitute

To get a defensible per-rating-band blunder taxonomy in Bullet only for B21 only for the 800-1500 Chess.com target, I would need on the order of 200-500 such games per 200-point band. Reaching that volume from the MCP would require:

Sampling tens of thousands of random low-rating games via lichess-games (≈ 5 PGNs per call, ~3 seconds per call) just to harvest a few hundred B21 bullet games per band, then running engine analysis on each.
This comfortably exceeds the 60-minute hard cap specified in the project instructions, and the MCP's lichess-games endpoint already showed intermittent 502s and HTTP/2 stream errors during the probing phase, which would compound the runtime risk.

Producing an article from the few dozen B21 bullet games actually available in the band would be statistically unsound and would mislead readers — a direct violation of the project's "data-driven" requirement.

What I recommend

Broaden the time control to Blitz (or Blitz + Bullet combined). The grandmaster-guide dataset has materially more Smith-Morra blitz coverage and would support a credible 800-1500 per-band analysis. I am happy to run that immediately on request.
Broaden the opening scope (e.g., entire Open Sicilian or all anti-Sicilians) while keeping Bullet, which would also yield enough per-band sample.
If Bullet + B21 specifically is required, the project would need either a fresh MCP data load that includes ECO/time-class filters on lichess-games, or whitelisted access to the Lichess Opening Explorer / Lichess game export API.

Per the project instruction "if the task takes more than 60 minutes, create the article with the data u have or error out saying its not possible" and "if any of the tools in the grandmaster-guide mcp goes down, error out, don't attempt to finish analysis without it", I am erroring out rather than producing a thin article.

Chess Coach — 21 April 2026

Frequently Asked Questions

Why did the Smith-Morra Gambit analysis get halted?

The analysis was stopped because there was not enough reliable data to support a credible blunder taxonomy. The available sample was too small for Bullet games in the relevant rating range.

What opening was the article trying to study?

It was focused on the Smith-Morra Gambit, which is ECO B21. The goal was to identify the most common blunders by Black in Bullet chess.

Why wasn't the data enough for a rating-based analysis?

The dataset did not provide enough Smith-Morra Bullet games split by rating band. The article notes that hundreds of games per 200-point band would be needed for a defensible result.

How many Smith-Morra games were found in the dataset?

The opening-deep-stats check returned 8,078 total Smith-Morra games across all ratings and time controls. However, only 315 of those were tagged as Bullet.

Could the analysis use Lichess data instead?

Not reliably in this setup. The lichess-games endpoint did not support ECO or time-class filters, and the public Opening Explorer returned a 401 Unauthorized error from the sandbox.

Why was a random sample of sub-1500 games not enough?

A random sample of 100 sub-1500 games found zero Smith-Morra games. That showed the opening was too rare in the target pool to support a trustworthy Bullet-only study.

What would be needed to complete the analysis?

The article says roughly 200 to 500 relevant games per 200-point rating band would be needed. Without that volume, any blunder conclusions would be too weak to trust.