mediar-ai/packages/skills/skills/project-development

Project Development Methodology

Identify tasks suited to LLM processing, design pipelines, and iterate with agent-assisted development.

Prerequisites

• Understanding of LLM capabilities
• Familiarity with batch processing

Instructions

Task-Model Fit

LLM-suited tasks:

• Synthesis across sources
• Subjective judgment with rubrics
• Natural language output
• Error tolerance acceptable
• Batch processing (no conversational state)

LLM-unsuited tasks:

• Precise computation
• Real-time requirements
• Perfect accuracy required
• Sequential dependencies
• Deterministic output needed

Manual Prototype First

Before building automation:

1. Copy one representative input into model
2. Evaluate output quality
3. Identify failure modes
4. Estimate tokens per item

If manual prototype fails, automated system will fail.

Pipeline Architecture

acquire → prepare → process → parse → render

• acquire: Fetch raw data
• prepare: Transform to prompt format
• process: LLM calls (expensive, non-deterministic)
• parse: Extract structured data
• render: Generate final outputs

File System as State Machine

data/{id}/
├── raw.json      # acquire complete
├── prompt.md     # prepare complete
├── response.md   # process complete
├── parsed.json   # parse complete

Check file existence to determine processing state.

Architectural Reduction

Start minimal. Vercel's d0 agent: 17 tools → 2 tools (bash + SQL), 80% → 100% success rate.

When reduction works:

• Data layer is well-documented
• Model has sufficient reasoning
• Specialized tools were constraining

Guidelines

1. Validate task-model fit with manual prototype
2. Structure pipelines as discrete, idempotent stages
3. Use file system for state management
4. Design prompts for parseable outputs
5. Start minimal; add complexity only when proven necessary
6. Estimate costs early and track throughout

Notes

• Karpathy's HN Capsule: 930 items, $58 cost, 1 hour
• Expect multiple architectural iterations
• Test whether scaffolding helps or constrains model

Source: muratcankoylan/Agent-Skills-for-Context-Engineering