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Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
Passed 19 of 21 test cases with the skill, and 4 of 21 without it.
and 24 more in the full report
16 fixed4 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
In `ThreadBidirectionalLearner`, after extracting features in `encode-thread`, under what dict key in `read-patterns` is the computed feature dictionary saved?
| Checked | Without skill | With skill |
|---|---|---|
| Stores feature dictionary under key "latest" inside self.read-patterns. | Missed | Passed |
The instructions your model reads when the skill loads.
Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
Version: 1.1.0 (music-topos enhanced) Trit: +1 (Generator - produces learned patterns) Bundle: learning
Agent-o-rama trains learning agents on interaction sequences to discover behavioral patterns. It extracts temporal, topic, and network patterns from raw interaction data, producing models compatible with the cognitive-surrogate skill.
CREATE TABLE learned_patterns (
pattern_id VARCHAR PRIMARY KEY,
pattern_type VARCHAR, -- 'temporal', 'topic', 'network', 'skill'
pattern_data JSON,
confidence FLOAT,
learned_at TIMESTAMP,
seed BIGINT -- SPI seed for reproducibility
);
-- Temporal pattern query
SELECT
EXTRACT(HOUR FROM created_at) as hour,
EXTRACT(DOW FROM created_at) as day_of_week,
COUNT(*) as post_count,
AVG(response_time_minutes) as avg_response_time
FROM interactions
GROUP BY hour, day_of_week
ORDER BY post_count DESC;
test cases passed, vs 4 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.