uni-store-pattern

name	uni-store-pattern
description	Store a reusable implementation pattern in Unimatrix. Use when you discover a gotcha, trap, or reusable solution that future agents should know.

Store Pattern — Implementation Knowledge

What This Skill Does

Stores a reusable pattern in Unimatrix. Patterns capture implementation gotchas, traps, and solutions — knowledge invisible in source code that you only learn by hitting it. They surface in future /uni-query-patterns results so the next agent doesn't repeat the discovery.

Use when: you discover something that compiles but breaks at runtime, a non-obvious integration requirement, a crate-specific trap, or a reusable solution to a recurring problem.

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Pattern vs Lesson vs Procedure

Type	When to use	Example
Pattern (/uni-store-pattern)	Reusable solution or gotcha applicable regardless of failure context	"Don't hold lock_conn() across await — deadlocks under concurrent requests"
Lesson (/uni-store-lesson)	Triggered by a specific failure; takeaway is preventive	"Gate 3b failed because rust-dev didn't read ADR before implementing"
Procedure (/uni-store-procedure)	Ordered steps to accomplish a task	"How to add a new MCP tool: step 1, 2, 3..."

Decision rule: If the knowledge was triggered by a specific failure and the takeaway is "don't do X," use /uni-store-lesson. If the knowledge is a reusable solution applicable regardless of failure context — "when doing X, use approach Y because Z" — use /uni-store-pattern.

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How to Store

Step 1: Check for existing patterns in the same area

mcp__unimatrix__context_search({
  "query": "{what the pattern is about}",
  "category": "pattern",
  "k": 3
})

If a matching pattern already exists, go to Step 2b (supersede) instead of creating a duplicate.

Step 2a: Store NEW pattern (no prior exists)

Assemble the content from three required fields:

• What: The pattern in one sentence (max 200 chars). What to do or not do.
• Why: What goes wrong without it (min 10 chars). The consequence that makes this worth knowing.
• Scope: Where it applies — crate name, module, or context.

mcp__unimatrix__context_store({
  "title": "{concise what statement}",
  "content": "What: {what}\nWhy: {why}\nScope: {scope}",
  "topic": "{crate name or module — e.g., 'unimatrix-store'}",
  "category": "pattern",
  "tags": ["{domain}", "{feature_cycle if known}"],
  "agent_id": "{your role name, e.g. uni-rust-dev}"
})

Step 2b: Supersede EXISTING pattern (prior exists but is incomplete or outdated)

mcp__unimatrix__context_correct({
  "original_id": 1234,  // integer — never quote it
  "content": "What: {updated what}\nWhy: {updated why}\nScope: {updated scope}",
  "reason": "Updated: {what changed and why}"
})

This deprecates the old pattern and creates a corrected version with a supersession chain.

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Quality Rules

Reject if:

• why is missing or under 10 characters — no motivation, no value
• what exceeds 200 characters — not concise enough
• Content is API documentation, not a gotcha — "Store has a lock_conn() method" is docs, not a pattern

Good patterns:

What: Don't hold lock_conn() across await points
Why: Deadlocks under concurrent MCP requests — the Store mutex is not async-aware
Scope: unimatrix-store, any async caller

What: Use #[serde(default)] on all new EntryRecord fields
Why: Existing serialized records lack the field; deserialization panics without default
Scope: unimatrix-core EntryRecord, any schema evolution

Bad patterns:

What: I used Arc::clone for shared ownership
Why: It works

(No gotcha. No consequence. This is just Rust basics.)

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Tagging Conventions

Tag type	Examples
Crate	store, server, vector, core, embed, engine
Domain	async, serialization, migration, mcp, confidence
Feature cycle	vnc-009, crt-005 (for retro traceability)

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Who Stores Patterns

Agent	When
uni-rust-dev	Implementation gotchas discovered while coding
uni-tester	Test infrastructure patterns, fixture usage discoveries
uni-risk-strategist	Risk patterns that recur across features
uni-researcher	Technical landscape patterns from problem space exploration
uni-vision-guardian	Recurring alignment variance patterns across features
uni-validator	Quality patterns (cross-feature, not gate-specific)
Retrospective agents	Patterns extracted from shipped feature analysis