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 skills/sethdford/claude-skills/integration-patternsnpx skills add sethdford/claude-skills --skill integration-patternsgit clone --depth 1 https://github.com/sethdford/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sethdford/claude-skills/integration-patterns)<a href="https://agentmods.dev/skills/sethdford/claude-skills/integration-patterns"><img src="https://agentmods.dev/badge/skills/sethdford/claude-skills/integration-patterns.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00040 | $0.00632 |
| Opus 5 | $0.00020 | $0.00316 |
| Sonnet 5 | $0.00008 | $0.00126 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
integration-patterns 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 6d ago.
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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Integration Patterns
Design robust data integrations between systems using time-tested patterns and technologies.
Context
You are integrating data from multiple systems. Analyze source systems, target requirements, consistency constraints, and operational overhead. Read existing integration code or architecture documents.
Domain Context
Based on Gregor Hohpe's Enterprise Integration Patterns and modern streaming:
- ETL (Extract-Transform-Load): Scheduled batch jobs; simple but high latency
- ELT (Extract-Load-Transform): Load raw data first, transform in warehouse; flexible but storage intensive
- CDC (Change Data Capture): Capture database changes in realtime; high fidelity but complex
- Event Streaming: Publish domain events to message brokers; loosely coupled but at-least-once semantics
- API-Based Integration: Synchronous queries; simple but tightly coupled and slower
Instructions
-
Choose Primary Pattern: Batch ETL (cost-effective, simple)? CDC (realtime, high fidelity)? Event streams (loosely coupled, asynchronous)? Synchronous APIs (simple, tight coupling)? Often hybrid approach.
-
Design Idempotency: Ensure processing same data twice yields same result. Use unique identifiers, deduplication logic, or transactional sinks.
-
Handle Schema Evolution: Source schema changes. Build transformation layer that's resilient to new fields, deprecated fields, type changes.
-
Implement Error Handling: Poison pill messages, dead-letter queues, circuit breakers. Log failures with context for debugging and replay.
-
Plan Monitoring and Alerting: Track pipeline freshness (time since last successful run), volume anomalies, latency, error rates. Alert on SLA violations.
Anti-Patterns
- Direct Database-to-Database Integration: Source DB talks directly to sink. Result: tight coupling, hard to recover from failures, operational complexity. Guard: Introduce message queue or ETL layer for decoupling.
- No Idempotency Guarantees: Retry logic assumes exactly-once delivery. Result: duplicate data, inconsistency. Guard: Always design for at-least-once; implement idempotency at sink.
- Ignoring Backpressure: Source pushes data faster than sink can consume. Result: memory buildup, crashes. Guard: Implement queueing, rate limiting, or load shedding.
- Monolithic Transformation Logic: All business logic in single transformation. Result: hard to test, reuse, evolve. Guard: Break into modular stages; test each independently.
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.
- 6d ago First seen · 48 lines · 40 tokens per session scan A 27bc8270f52f
integration-patterns is a skill published in the GitHub repository sethdford/claude-skills (38 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 632 once invoked, about $0.0002 per session on Opus 5. 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 2026-08-30.
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