v1truv1us Default output: return only the result, blockers, and required evidence. Omit preambles, process narration, repeated context, confidence scores, and follow-up offers. Use at most five bullets unless a required artifact or schema needs more.
Continuous Learning
Overview
Learn from sessions in two complementary ways:
- Instinct-based learning — extract reusable patterns, score confidence, promote high-confidence instincts into skills.
- Workspace memory — delegate durable preferences and facts to the
agents-memory-updatersubagent (orchestration only in this skill).
When to Use
- After completing a significant feature or fix (instincts)
- When a session revealed a non-obvious solution worth remembering
- Before starting similar work to apply learned instincts
- When transcript deltas may update
AGENTS.md(workspace memory)
Instinct Lifecycle
1. Discovery
When a pattern is encountered during work:
Pattern: [What was discovered]
Context: [When this applies]
Confidence: [0.0-1.0 based on evidence]
Evidence: [What proves this works]
2. Validation
Before storing an instinct:
- Pattern has been verified in at least one successful outcome
- Context is specific enough to avoid false positives
- Confidence score is justified with evidence
- No conflicting instincts exist
3. Storage
Instincts are stored with:
instinct:
name: "descriptive-name"
pattern: "what to do"
context: "when to apply"
confidence: 0.85
evidence: "why this works"
created: "2026-01-15"
usage_count: 3
success_rate: 0.95
4. Evolution
When an instinct reaches thresholds:
- Confidence > 0.9 AND usage_count > 5 AND success_rate > 0.9 → Promote to skill
- Confidence < 0.5 AND usage_count > 3 → Deprecate
- Confidence unchanged after 30 days → Review
Confidence Scoring
| Score | Meaning | Action |
|---|---|---|
| 0.9-1.0 | Proven pattern, multiple successes | Promote to skill candidate |
| 0.7-0.9 | Strong pattern, some evidence | Use with confidence |
| 0.5-0.7 | Plausible pattern, limited evidence | Use cautiously, verify |
| 0.3-0.5 | Weak pattern, speculative | Note but don't rely on |
| 0.0-0.3 | Unproven, likely incorrect | Discard |
Import and Export
Export Instincts
Export all instincts to JSON: [{name, pattern, context, confidence, evidence}]
Import Instincts
Import instincts from JSON. Merge with existing records and update confidence on duplicates.
Workspace memory (AGENTS.md)
When transcript mining may produce durable updates—not one-off task context:
- Call
agents-memory-updater; return its result unchanged. - Do not mine transcripts or edit files in the parent flow.
The updater owns AGENTS.md sections (## Learned User Preferences, ## Learned Workspace Facts), incremental transcript indexes under ~/.cursor/projects/<workspace-slug>/agent-transcripts/, and deduplication (max 12 bullets per learned section).
If no meaningful updates: respond exactly No high-signal memory updates.
Anti-Rationalization Table
| Excuse | Counter |
|---|---|
| "I'll remember this pattern" | Human memory is unreliable. Document it now with context and evidence. |
| "This is too specific to be useful" | Specific patterns become general skills through evolution. Start specific, generalize later. |
| "I don't have time to document" | Two minutes now saves hours of rediscovery later. Use the instinct template. |
| "The confidence score is subjective" | Confidence is a starting point. Usage and success rates provide objective data over time. |