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Checkpoint state before risky operations, detect anomalies, and recover gracefully
Passed 19 of 22 test cases with the skill, and 12 of 22 without it.
and 9 more in the full report
7 fixed12 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
An asset processing batch completed 85% of target files, but 15% failed due to missing source images. The calculated usefulness of the generated assets exceeds our minimum acceptance threshold. Should we discard all progress and restore state, or keep the partial result?
| Checked | Without skill | With skill |
|---|---|---|
| Returns PARTIAL execution status when output value exceeds threshold. | Missed | Passed |
| Archives state checkpoint upon partial success above threshold. | Missed | Passed |
The instructions your model reads when the skill loads.
FUNCTION checkpoint_and_recover(task, execute_fn):
// Pre-execution checkpoint
checkpoint = {
timestamp: now(),
task_id: task.id,
state: capture_current_state(),
files_modified: [],
outputs_produced: []
}
save_checkpoint(checkpoint)
TRY:
// Execute with monitoring
monitor = SPAWN execution-monitoring(task)
result = execute_fn(task)
// Post-execution validation
IF monitor.anomalies_detected:
RAISE AnomalyError(monitor.anomalies)
END
// Validate result integrity
validated = SPAWN result-collection(result, task.success_criterion)
IF validated.complete AND validated.consistent:
// Success — archive checkpoint (keep for audit trail)
archive_checkpoint(checkpoint)
RETURN {status: DONE, result: validated}
ELSE:
// Partial success — decide whether to keep or rollback
IF validated.partial_value > threshold:
archive_checkpoint(checkpoint)
RETURN {status: PARTIAL, result: validated, missing: validated.gaps}
ELSE:
restore_state(checkpoint)
test cases passed, vs 12 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.