Continuous Learning Skill

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-updater subagent (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. |

Agent Skills: Continuous Learning

Install this agent skill to your local

Skill Files