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You must strictly adhere to the project rules defined in `docs/agents/agent_instructions.md`. Read this file before making any significant architectural, geospatial data processing changes, or general code modifications. Use `read_file` to load `docs/agents/agent_istructions.md`.
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You must strictly adhere to the project rules defined in [docs/agents/agent_instructions.md](../docs/agents/agent_instructions.md). Read this file before making any significant architectural, geospatial data processing changes, or general code modifications. Use `read_file` to load [docs/agents/agent_instructions.md](../docs/agents/agent_instructions.md).
You must strictly adhere to the project rules defined in `docs/agents/agent_instructions.md`. Read this file before making any significant architectural, geospatial data processing changes, or general code modifications.
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You must strictly adhere to the project rules defined in [docs/agents/agent_instructions.md](../docs/agents/agent_instructions.md). Read this file before making any significant architectural, geospatial data processing changes, or general code modifications.
You must strictly adhere to the project rules defined in `docs/agents/agent_instructions.md`. Read this file before making any significant architectural, geospatial data processing changes, or general code modifications.
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You must strictly adhere to the project rules defined in [docs/agents/agent_instructions.md](docs/agents/agent_instructions.md). Read this file before making any significant architectural, geospatial data processing changes, or general code modifications.
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@@ -14,20 +14,13 @@ Yes, these instructions are more prescriptive than *current* best practices, but
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The `instructions/` folder contains specific skill files that guide the agent's behavior for particular tasks. Here is a summary of each skill, its purpose, and when to use it:
|`analytics.md`| Extracts truth from experimental data with statistical rigor. | Use for Exploratory Data Analysis (EDA) and visualization to ensure reproducibility and prevent misleading claims. |
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|`formal_planning.md`| Enforces a structured planning protocol via a Formal Design Document. | Use when explicitly asked for a plan, architecture, or proposal to map out scope, trade-offs, and steps before coding. |
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|`infrastructure.md`| Manages reproducible and resilient environments/pipelines as code. | Use for containerization (Docker), HPC/SLURM cluster setup, or CI/CD tasks to ensure fault tolerance and exact dependency pinning. |
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|`KNOWLEDGE.md`| A centralized repository for project-specific tribal knowledge. | Use to document or consult specific findings, library quirks, or architectural decisions to avoid repeating past mistakes. |
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|`ml.md`| Builds state-of-the-art, reproducible, and reliable machine learning pipelines. | Use for ML model training, evaluation, and experiment management to guarantee strict data isolation and deterministic execution. |
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|`orchestrator.md`| Focuses on horizontal integration and strategic decomposition of goals. | Use for multi-component tasks to define explicit contracts between modules and ensure end-to-end flows work correctly. |
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|`plan_to_tasks.md`| Decomposes high-level plans into modular, atomic, and verifiable tasks. | Use when transitioning from planning to execution to ensure each step has clear context, acceptance criteria, and testing protocols. |
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|`python.md`| Elevates Python scripts into robust, maintainable, and type-safe software. | Use for all Python development and QA to enforce strict typing, SOLID principles, vectorization, and automated workflows. |
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|`root_cause_analysis.md`| Systematically diagnoses and permanently fixes software failures. | Use when presented with a bug, traceback, or unexpected result to isolate the failure (MRE) and target the actual root cause. |
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|`security.md`| Identifies vulnerabilities, enforces defense-in-depth, and ensures data privacy. | Use for tasks involving authentication, untrusted input, or infrastructure to prevent injection attacks and hardcoded secrets. |
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|`specdrivendev.md`| Implements lightweight Spec-Driven Development to define contracts first. | Use when starting a new feature to define data structures, signatures, and docstrings before writing logic, preventing LLM hallucinations. |
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|`systemdesign.md`| Designs systems that are maintainable, evolvable, and robust. | Use for architectural decisions to enforce separation of concerns, configuration-first design, and proper dependency injection. |
|`planning.md`| Combined Planning, Specification (SDD), and Task Decomposition Protocol. | Use for any multi-step implementation to map out scope, define technical contracts (SDD), and break down work into atomic tasks. |
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|`software-dev.md`| Unified Software Development, ML, Analytics & Infrastructure Protocol. | Use for Python development, system design, ML/geospatial processing, data analysis, and infrastructure/environment management. |
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|`review.md`| Harsh Security & Architecture Review Protocol. | Use to identify vulnerabilities (tokens, paths, SSL) and tear apart implementations for performance bottlenecks and architectural rot. |
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|`root_cause_analysis.md`| Systematically diagnoses and permanently fixes software failures. | Use when presented with a bug, traceback, or unexpected result to isolate the failure (MRE) and target the actual root cause. |
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|`KNOWLEDGE.md`| A centralized repository for project-specific tribal knowledge. | Use to document or consult specific findings, library quirks, or architectural decisions to avoid repeating past mistakes. |
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## How to use them
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In practice... it's not always the case. It is probably better to manually feed the instructions directly to the agent/tool as context in your prompt just to make sure:
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```text
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Using @docs/agents/agent_instructions.md, @docs/agents/instructions/python.md, and @docs/agents/instructions/systemdesign.md and @docs/agents/instructions/formal_planning.md, create a plan for a new class that will ...
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Using @docs/agents/agent_instructions.md, @docs/agents/instructions/software-dev.md, and @docs/agents/instructions/planning.md, create a plan for a new class that will ...
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```
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When using models with smaller context windows, it will also be important to clear the context once in a while to ensure better results.
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It's usually a good thing to clear/compress the context once in a while to ensure better results.
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For example:
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### Workflow example
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- Create plan
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- Manually revise plan document
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- Clear context
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- Ask agent to implement first step of the plan
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- Clear context
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- Repeat
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First, define **what** you want to do, **how** and **why**. Go in as much detail as you can. Let's call this your *preliminary design document*.
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You can also do this step through a chat interface with an LLM so you can brainstorm, ask questions, investigate starting points, development directions and library/tool selections.
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Once you have your *preliminary design document*, you are ready to start using your agent.
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