Evidence And Artifacts
The project treats artifacts as audit hygiene. They are the way to check what a run did, not the research contribution by themselves. This matters because LLM text can sound successful even when Minecraft state did not change.
For the active capability-gated social sandbox, artifacts should support independent review of individual task competence, goal continuity, interdependent scenario conditions, and long-run social behavior. The common observation unit remains:
state_before + executed_action + observed_delta + evidence_refs
Optional prediction or analysis artifacts stay separate from runtime truth, so the actor's expected outcome and provider rationale never become ground truth. Videos and screenshots are synchronized review surfaces, not substitutes for the structured row and verifier evidence.
What Counts As Evidence
Useful evidence includes:
- transcript records;
- Mineflayer action attempts and results;
- inventory, position, block, container, entity, or chat observations;
- verifier output;
- world-state scan summaries with explicit scan limits;
- actor workspace evidence references;
- provider input/output snapshots;
- provider usage records when live models are used;
- response-window records showing when another actor had a chance to respond;
- public-history exports that include only allowlisted runtime evidence;
- offline prediction/scoring artifacts after label lock.
What Does Not Count Alone
These are context, not proof of Minecraft progress:
- model rationale;
- memory notes;
- repeated
observeorwait; - animation or partial motion;
- a generated source file that has not passed a bounded trial;
- a summary that lacks a backing artifact.
Failure Is A Result
Blocked, failed, and environment-blocked runs are useful when they explain the reason clearly. A good report should say whether the actor was blocked by missing parameters, unavailable world state, repeated target failure, provider budget, auth, server lifecycle, or runtime checks.
Why This Helps The Experiment
The active experiment needs consequences that a reviewer can inspect. If an actor promises help, fails to gather resources, lends a tool, refuses a request, places a public affordance, or repeats an impossible action, later turns should see artifact-backed consequences instead of relying on a fresh prompt summary.
The research question is not whether artifacts are neat. It is whether public interaction history adds predictive signal for another actor's observable social/material response, after simple baselines and leakage checks have had a fair chance to erase the claim.