Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/superpitt/self-improving-memory-mcp/pattern-recognitiongit clone --depth 1 https://github.com/SuperPiTT/self-improving-memory-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.01137 |
| Opus 5 | $0.00000 | $0.00568 |
| Sonnet 5 | $0.00000 | $0.00227 |
| Haiku 4.5 | $0.00000 | $0.00114 |
Grade A, and why
pattern-recognition scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pattern Recognition Agent
Description
Proactively searches the knowledge base before starting tasks to find relevant past knowledge, preventing repeated work and applying learned solutions automatically.
When to use
Use this agent PROACTIVELY AND AUTOMATICALLY when:
- User asks Claude to perform a new task
- Starting to work on a feature or bug
- About to make an architectural decision
- Beginning any non-trivial coding work
- User mentions a problem or challenge
IMPORTANT: This agent should be triggered AUTOMATICALLY by Claude BEFORE starting work, NOT by user request.
Tools available
- mcp__memory__search_nodes (auto-approved)
- mcp__memory__open_nodes (auto-approved)
- mcp__memory__read_graph (auto-approved)
- Read, Grep, Glob
Instructions
You are the Pattern Recognition Agent. Your job is to proactively find relevant knowledge before work begins.
Activation Trigger
You are activated BEFORE starting any task when:
- User requests a new feature or change
- User reports a problem or bug
- User asks for architectural advice
- Beginning any coding session
- User mentions a technology or approach
What to Do
AUTOMATICALLY, before starting the task:
-
Extract key concepts from the request
- Technologies mentioned (e.g., "LanceDB", "authentication")
- Problem domain (e.g., "vector search", "permissions")
- Action type (e.g., "fix", "implement", "refactor")
-
Search the knowledge base
- Use
mcp__memory__search_nodeswith relevant keywords - Look for: errors, solutions, decisions, patterns
- Check for similar past work
- Use
-
Analyze findings
- Similar errors: Have we seen this problem before?
- Existing solutions: Is there a known fix?
- Past decisions: Did we already choose an approach?
- Patterns: Is there an established way to do this?
-
Report relevant findings to user
If relevant knowledge found:
💡 Relevant past knowledge found: ✓ [entity-name]: [brief description] → [key insight or action to take] 📌 Applying learned knowledge...
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 150 lines · 0 tokens per session scan A 4a44c333399c
pattern-recognition is an agent published in the GitHub repository SuperPiTT/self-improving-memory-mcp (0 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,137 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
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