flockion

Plugin flockion from marketplace flockion in error505/Flockion_AI_Engineering. Commands read from the repo's manifest — 18 days ago.

Skills (16)

• flockion_agent_design

  Designs production-grade Flockion agents and agent teams with clear purpose, input/output contracts, narrow tools, memory rules, handoffs, guardrails, observability, cost control, and human approval for risky actions. Use when creating, reviewing, or improving agents, teams, prompts, tools, skills,

• flockion_architecture_review

  Reviews proposed architecture for Flockion using practical engineering: simplest working design, clear boundaries, secure defaults, observability, cost awareness, and no speculative infrastructure. Use for Azure, FastAPI, React, PostgreSQL, Service Bus, storage, agent orchestration, RAG, and event-d

• flockion_cloud_patterns

  Picks the smallest cloud design pattern that solves a named problem, and refuses to add one without a named constraint. Covers the full Azure Well-Architected catalog (43 patterns: Circuit Breaker, Retry, Bulkhead, CQRS, Event Sourcing, Saga, Sidecar, Ambassador, Gateway Routing/Aggregation/ Offload

• flockion_code_review

  Reviews Flockion code, diffs, pull requests, generated files, and refactors for correctness, simplicity, maintainability, file size, type safety, accessibility, security, observability, and overengineering. Use for TypeScript, React, Python, APIs, agents, YAML, Bicep, GitHub Actions, and cloud autom

• flockion_cost_control

  Reviews and improves AI, token, cloud, database, storage, queue, logging, and execution costs for Flockion. Use when designing agents, teams, RAG, model usage, Azure resources, GitHub Actions, background jobs, streaming, caching, batching, or usage-based pricing.

• flockion_decomposition

  Breaks a monolith into services the lazy, safe way — only when there is real pressure, one reversible seam at a time, using incremental patterns (strangler fig, branch by abstraction, parallel run, expand–migrate–contract data migrations, anti-corruption layer, event interception) instead of a big-b

• flockion_engineering_abap

  Forces the simplest, shortest, safest ABAP solution that actually works. Lazy senior-engineer pragmatism for SAP ABAP — classic ABAP, modern ABAP (7.40+), ABAP Cloud / clean core, ABAP SQL, CDS views, RAP and EML, OO ABAP, internal tables, exceptions, and ABAP Unit. Use the SAP standard and released

• flockion_engineering_ai

  Forces the simplest, shortest, safest AI solution that actually works. Lazy senior-engineer pragmatism for LLM features, agents, RAG, tool-calling, and prompts. Use a prompt before a chain, retrieval before fine-tuning, deterministic code before an agent, and one tool before a tool framework. Keep c

• flockion_engineering_data

  Forces the simplest, shortest, safest data solution that actually works. Lazy senior-engineer pragmatism for SQL, databases, schema design, migrations, and data pipelines. Use the database before application code, a plain query before an ORM dance, an index before a cache, and one reversible migrati

• flockion_engineering_infra

  Forces the simplest, shortest, safest infrastructure that actually works. Lazy senior-DevOps pragmatism for IaC, CI/CD, containers, and cloud automation: Bicep, Terraform, GitHub Actions, Docker, Kubernetes, shell. Use managed platform features before custom infra, official actions before bespoke pi

• flockion_engineering_python

  Forces the simplest, shortest, safest solution that actually works. Combines lazy senior-developer pragmatism with practical clean-code engineering for Python, backend, APIs, cloud platforms, AI agents, orchestration services, YAML workflows, and infrastructure automation. Use existing code before n

• flockion_engineering_typescript_react

  Forces the simplest, shortest, safest solution that actually works for Flockion engineering work. Combines lazy senior-developer pragmatism with practical clean-code standards for TypeScript, React, frontend, Python, backend, APIs, cloud platforms, AI agents, orchestration services, YAML workflows,

• flockion_engineering

  Base engineering standard for Flockion. Forces the simplest, shortest, safest solution that actually works across TypeScript, React, Python, backend, APIs, cloud platforms, AI agents, orchestration services, YAML workflows, and infrastructure automation. Use existing code before new code, native pla

• flockion_iso_27001

  Maps Flockion features, code, agents, APIs, cloud resources, and workflows to ISO/IEC 27001:2022 Annex A controls. Use when building or reviewing anything that touches access control, secrets, logging, data retention, encryption, supplier/third-party risk, change management, incident handling, or ev

• flockion_product_builder

  Turns a product idea into the smallest useful Flockion feature that can be shipped, tested, and improved. Forces MVP thinking, user-value clarity, minimum data model, minimum API, minimum UI, and clear success metrics. Use when defining new features, agent marketplace concepts, MVPs, user flows, mon

• flockion_security_review

  Reviews Flockion features, code, agents, tools, APIs, cloud resources, authentication, authorization, tenant isolation, secrets, prompt injection, data access, audit logging, and risky workflows. Use before exposing functionality to users, production systems, external tools, or marketplace agents.

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