instinct-system

name

instinct-system

description

Unified learning-and-memory system: confidence-scored instincts (observe-hypothesize-confirm, stored in .claude/instincts.md), user corrections captured as permanent rules in MEMORY.md, and organic discoveries logged to .claude/learning-log.md. Includes status, export, and import modes. Load this skill when you notice a recurring pattern, a user corrects your output, or you discover something non-obvious. Triggers: "show instincts", "what have you learned", "list instincts", "export instincts", "share instincts", "import instincts", "load instincts from", "learn this", "I think they always", "notice a pattern", "instinct", "hypothesis", "confidence", "learn from mistakes", "remember this", "don't do that again", "log this", "document this finding", "gotcha", "what did we learn", "learnings", "discoveries", or at session start (to load existing knowledge).

Instinct System

One learning system, three tiers. Every signal Claude receives during work — an observed pattern, a user correction, a surprising discovery — routes to exactly one store.

Core Principles

1. Three tiers, one routing decision — Instincts are unconfirmed hypotheses (.claude/instincts.md). Corrections are user-confirmed rules (MEMORY.md). Discoveries are insights that explain the world (.claude/learning-log.md). Rules prescribe behavior; insights describe it; instincts are rules-in-waiting. Never mix the tiers — a hypothesis in MEMORY.md pollutes permanent knowledge, and a confirmed rule left as an instinct gets forgotten.

2. Instincts are hypotheses, not rules — An instinct starts as a guess from a single observation and has no authority until confirmed. "One handler uses sealed" is an instinct at 0.3; "all 12 handlers use sealed" is a rule at 0.9. Confidence (0.3–0.9) drives behavior: note at 0.3, mention at 0.5, follow at 0.7, promote at 0.9.

3. A user correction is a confirmed instinct at full confidence — When the user corrects you, skip the confirmation cycle entirely. Generalize the lesson, capture it immediately in MEMORY.md with the "why", and confirm what was captured. A correction costs the user 30 seconds today and saves hours across all future sessions — losing one is the most expensive mistake this system can make.

4. Project-scoped, never global — What holds in one codebase may be wrong in another. Instincts live per-project; transfers between projects go through export/import with confidence decay, never at full confidence.

5. Review at session start, prune periodically — Read MEMORY.md and load instincts at 0.7+ before writing any code; scan recent log entries for the working area. Knowledge captured but never reviewed is wasted effort. Audit all three stores when they bloat — stale instincts, duplicate rules, and unreviewed logs defeat the purpose.

Patterns

Tier Routing

Signal	Destination	Lifespan
Pattern observed, not yet confirmed ("I think they always...")	.claude/instincts.md at 0.3	Until promoted or discarded
User correction ("no, use X", "don't do that again", "remember this")	MEMORY.md immediately, generalized	Permanent until proven wrong
Instinct reaching 0.9 confidence	Promote to MEMORY.md, remove from instincts	Permanent
Non-obvious discovery (bug root cause, gotcha, workaround, perf finding)	.claude/learning-log.md	3–6 months, then archive or promote
Same gotcha logged 3+ times	Promote to MEMORY.md as a preventive rule	Permanent
Session state (done/pending)	Handoff via wrap-up — not this system	Until next session

Instinct Lifecycle (Observe-Hypothesize-Confirm)

1. OBSERVE     — "This handler is internal sealed class. Convention?"
2. HYPOTHESIZE — Write to .claude/instincts.md at confidence 0.3:
                 - Use `sealed` on handler classes | confidence: 0.3 | seen: 1 | last: 2026-06-12
3. SEEK        — Actively check 2-3 related files (find_symbol, get_public_api).
                 Passive observation is not enough.
4. ADJUST      — Confirmed: raise per the adjustment track.
                 Contradicted: halve confidence, note the exception.
                 Mixed: hold steady, note the split.
5. PROMOTE     — At 0.9, present evidence and offer promotion to MEMORY.md.

Instinct Storage Format

.claude/instincts.md, grouped by category with structured metadata:

# Project Instincts

## Code Style [0.7]
- Use `sealed` on all handler classes | confidence: 0.8 | seen: 5 | last: 2026-06-12
- Prefix private fields with underscore | confidence: 0.5 | seen: 2 | last: 2026-06-10

## Architecture [0.7]
- Feature folders use singular names | confidence: 0.7 | seen: 4 | last: 2026-06-12

Category header [0.7] = average confidence. Standard categories: Code Style, Architecture, Naming, Testing, Data Access, API Design, Configuration, Performance, Tooling.

Confidence Adjustment Rules

No ad-hoc scoring. Follow this track precisely:

CONFIRMATION:  1st observation → 0.3 | 2nd → 0.5 | 3rd → 0.7 | 4th → 0.8
               5th+ with zero contradictions → 0.9 (promotion candidate)

CONTRADICTION: Any contradiction → halve current confidence (0.7 → 0.35)
               Two in a row → 0.1 (effectively dead)

USER OVERRIDE: Explicit confirm → 0.8 | Explicit correct → 0.0 (remove,
               capture in MEMORY.md instead) | "Sometimes" → cap at 0.5

STALENESS:     No observations for 10+ sessions → flag for review
               Contradicted, unreconfirmed for 5 sessions → remove

Acting on Instincts by Confidence

0.0–0.2 → IGNORE  — insufficient evidence, do not mention
0.3–0.4 → NOTE    — record internally, do not apply
0.5–0.6 → MENTION — "This project may use [pattern]. Follow it?"
0.7–0.8 → FOLLOW  — apply by default, mention on first use
0.9     → PROMOTE — offer to add to MEMORY.md as a permanent rule

Never silently apply an instinct below 0.7.

Correction Capture Flow (Tier 2)

When the user corrects your output ("no, use X instead", "we don't do it that way", "always/never do X", "remember this"):

1. DETECT      — Recognize the correction signal.
2. ACKNOWLEDGE — "Got it — HybridCache instead of IMemoryCache."
3. GENERALIZE  — Specific: "Don't use IMemoryCache in the Orders endpoint"
                 General:  "Always use HybridCache over IMemoryCache —
                            stampede protection + L1/L2 out of the box."
                 Ask: is this specific to this file? This layer? What's the
                 underlying principle? Store the broadest correct statement.
4. CHECK       — Scan MEMORY.md for overlap. Update an existing rule rather
                 than adding a near-duplicate.
5. STORE       — Write under the right category, one line, rationale after
                 the dash. If a matching instinct exists, remove it — it
                 just graduated.
6. CONFIRM     — "Added to Memory > Data Access: HybridCache over IMemoryCache."

MEMORY.md format — same categories as instincts, one actionable rule per line:

## Data Access
- Always use HybridCache over IMemoryCache — stampede protection + L1/L2
- Never use repository pattern over EF Core — use DbContext directly

Discovery Logging (Tier 3)

Log organic findings to .claude/learning-log.md the moment they occur — a 2-line entry written immediately beats a paragraph reconstructed later. Entry format:

## 2026-06-12 | Gotcha | MassTransit Consumer Registration Order Matters
Multiple consumers for one message type run in registration order; if the
first throws, the rest are skipped. Caused missed audit events.
**Files:** `src/Shared/Extensions/MassTransitConfig.cs:15-30`
**Resolution:** Independent consumer endpoints or the retry filter.

Log when (and only when) you hit one of these triggers:

Bug Root Cause        — the cause was NOT where the error appeared
Architecture Decision — discovered WHY something is built a certain way
Gotcha                — framework/library behaved surprisingly
Performance Discovery — unexpected perf behavior, with the measurement
Pattern Found         — reusable codebase pattern worth remembering
External Service      — third-party API behaves differently than documented

Those six trigger names are also the category vocabulary — use them verbatim in entries. Routine changes with nothing surprising do not get logged.

Session-Start Loading

1. Read MEMORY.md — apply rules proactively, don't wait to be reminded
2. Read .claude/instincts.md — load 0.7+ as defaults, note 0.5–0.6
3. Scan recent learning-log entries for the area you're working in
4. Flag stale instincts (10+ sessions without observation) for review

Modes

Three operations on the instinct store, invoked by name or trigger phrase.

Status ("show instincts", "what have you learned", "list instincts")

1. Read .claude/instincts.md; parse each entry's metadata.
2. Sort by confidence descending, group by category, render as a table: instinct | confidence | category | status (new / stable / reinforced / decaying / promotion candidate).
3. Summarize health: total count, average confidence, recently reinforced vs decaying entries, any conflicting instincts.

Export ("export instincts", "share instincts")

1. Read .claude/instincts.md; filter to confidence > 0.7 (threshold configurable).
2. Strip project-specific context (file paths, line numbers) while preserving the pattern itself.
3. Write to .claude/instincts-export.md with portable metadata.
4. Report what was exported and what was skipped (below threshold), with the output path.

Import ("import instincts", "load instincts from")

1. Read the export file (user-provided path or .claude/instincts-export.md) and the current .claude/instincts.md.
2. Merge each imported instinct:
   • No local match — add with confidence decayed by 0.2 (0.9 → 0.7); never import above 0.7. Mark source: imported from [project].
   • Matching instinct exists — keep the higher confidence, mark reinforced.
   • Conflicting instinct exists — present both to the user for resolution; do not auto-overwrite local evidence.
3. Write the merged result and report imported / merged / conflicts. Every project must confirm imported patterns locally.

Anti-patterns

Over-Eager Pattern Recognition

# BAD — first observation treated as a rule
*Reads one handler* "This project always uses internal sealed class."
*Generates 5 handlers that contradict 8 of 9 existing ones*

# GOOD — hypothesis at 0.3, then active confirmation
"Noticed internal sealed in CreateOrderHandler. Instinct at 0.3.
 Checking 3 more handlers..." *All public* → "Disconfirmed. Discarding."

Fixing Without Capturing

# BAD — correction applied, lesson lost
User: "No, we use HybridCache here"
Claude: "Fixed." *Next session: same mistake*

# GOOD — fix AND capture
Claude: "Fixed. Added to Memory > Data Access:
         Always use HybridCache over IMemoryCache."

Logging Everything

# BAD — noise entry
## 2026-06-12 | Pattern Found | Used Primary Constructors

# GOOD — only the non-obvious earns an entry
## 2026-06-12 | Gotcha | Primary Constructor Params Captured as Fields
Declaring an explicit field with the same name warns but compiles —
and the two can silently diverge.

Write-Only Stores

# BAD — 40 instincts at 0.3 from 3 months ago; MEMORY.md at 200 lines
  with duplicates; 500-line log nobody reads
# GOOD — periodic audit: remove instincts below 0.2 or stale 10+
  sessions; merge/prune MEMORY.md past 50 rules; every ~20 log entries,
  promote recurring findings and archive the stale. Keep instincts
  under 50 active entries.

Decision Guide

Scenario	Action
First time seeing a pattern	Instinct at 0.3, check 2-3 related files
Pattern seen 3+ times, no contradictions	Raise to 0.7, follow by default
Pattern contradicted	Halve confidence, note the exception
User says "we always do X"	Instinct at 0.8 (user confirmation)
User corrects your code	Generalize → MEMORY.md immediately; drop any matching instinct
User says "remember this" / "always/never"	Capture in MEMORY.md as stated, generalized
Same correction given twice	High priority — the rule wasn't captured or reviewed
Correction about a one-time task	Don't store — only reusable patterns
User asks to forget a rule	Remove from MEMORY.md immediately
Non-obvious bug, gotcha, workaround, perf surprise	Log to learning-log with category + files
Same gotcha logged 3+ times	Promote to MEMORY.md as a preventive rule
Instinct at 0.9	Present evidence, offer promotion to MEMORY.md
User partially confirms ("only for commands")	Narrow scope, reset to 0.5, re-confirm
Sharing patterns with another project	Export at 0.7+, import with 0.2 decay
Conflict during import	Present both to the user; never auto-overwrite
Any store bloats (50+ entries/rules)	Audit: prune dead, merge duplicates, promote mature
Starting a session	Load MEMORY.md, instincts 0.7+, recent log entries

Related

• convention-learner — detects codebase conventions in bulk; feed its findings in as instincts
• wrap-up — end-of-session ritual; routes session learnings into the correct tier of this system