Documentación integral de agentes, convenciones y backend con TDD para técnicas de prompting#193
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2-Coatl merged 10 commits intoNov 14, 2025
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… techniques - Created organized structure in .github/agents/ for all agent types - SDLC agents: planner, feasibility, design, testing, deployment - Automation agents: coherence analyzer, PDCA, constitution validator, metrics collector - DevOps agents: GitOps, release, dependency, security - LLM provider agents: Claude, ChatGPT, HuggingFace - Domain agents: API, UI, infrastructure, docs, scripts - Prompting techniques: 120+ documented, 20+ implemented - Auto-CoT, Self-Consistency, Chain of Verification, Tree of Thoughts - ReAct, RAG, Constitutional AI, Expert Prompting, etc. - Added comprehensive implementation mapping - All documentation without emojis as per project standards
…LC pipeline Complete SDLC execution for generating TDD tests for prompting techniques: ## SDLC Phases Completed (5/5) - Phase 1 (Planning): Issue generation, story points, acceptance criteria - Phase 2 (Feasibility): Risk analysis, dependency mapping, viability assessment - Phase 3 (Design): HLD/LLD, test architecture, fixtures design - Phase 4 (Testing): Test strategy, Auto-CoT and Self-Consistency application - Phase 5 (Deployment): Rolling deployment plan, CI/CD integration ## Tests Implemented (2/11 modules) - test_auto_cot_agent.py (25+ tests, 85%+ coverage estimate) * Initialization, clustering, demonstration generation * Zero-Shot CoT, sampling, quality scoring * Error handling, parametrized tests, integration tests - test_self_consistency.py (20+ tests, 85%+ coverage estimate) * Multiple response generation, majority voting * Consistency scoring, temperature effects * Edge cases, performance tests ## Test Infrastructure - conftest.py: 15+ shared fixtures * Mock LLM generators, sample data, configurations * Utility functions, pytest configuration * Auto-CoT and Self-Consistency specific fixtures - Directory structure: * scripts/coding/ai/tests/techniques/ - Unit tests * scripts/coding/ai/tests/fixtures/ - Test data * scripts/coding/ai/tests/integration/ - Integration tests ## Documentation (3,500+ lines) - SDLC_COMPLETE_RUN_TDD_PROMPTING_TECHNIQUES.md - Comprehensive summary - 01_planning_output.md - Planning phase artifacts - 02_feasibility_analysis.md - Risk analysis and mitigation - 03_design_hld_lld.md - High and low level design - 04_testing_strategy.md - Testing strategy with techniques - 05_deployment_plan.md - Deployment and rollback plans ## Techniques Applied - Auto-CoT: Generated complex test cases through reasoning chains - Self-Consistency: Validated test robustness through multiple paths - ReAct: Risk analysis with step-by-step reasoning - Expert Prompting: Architecture design from senior perspective - RAG: Retrieved best practices for test patterns ## Metrics - Story Points: 3/13 completed (18%) - Tests: 45+ test cases - Coverage: 85%+ (estimated for implemented modules) - Code: ~1,000 lines of test code - Documentation: ~3,500 lines ## Next Steps - Implement remaining 9 test modules - Execute tests locally and verify coverage - Configure CI/CD pipeline - Code review and iteration This establishes the foundation for complete TDD coverage of all prompting techniques in the project, following strict SDLC methodology.
- Renamed all SDLC phase documents to remove leading numbers: * planning/planning_output.md (was 01_*) * feasibility/feasibility_analysis.md (was 02_*) * design/design_hld_lld.md (was 03_*) * testing/testing_strategy.md (was 04_*) * deployment/deployment_plan.md (was 05_*) - Updated all references in SDLC_COMPLETE_RUN_TDD_PROMPTING_TECHNIQUES.md - Added comprehensive test use cases documentation: * test_use_cases.md with 54 test cases * 18 use cases total (10 AutoCoT + 8 SelfConsistency) * Detailed descriptions for each test case * Input/output specifications * Expected results and verifications Test use cases cover: - AutoCoTAgent: 28 test cases across 10 use cases * Initialization, clustering, demonstrations * Zero-Shot CoT, sampling, quality scoring * Error handling, parametrized tests, integration - SelfConsistencyAgent: 26 test cases across 8 use cases * Initialization, generation, voting * Consistency scoring, execution * Error handling, performance, utilities All documentation now follows project convention without numbering.
ISSUE: Documentation was incorrectly placed in docs/agent/ directory CORRECTION: All SDLC and testing documentation moved to docs/backend/ - SDLC_COMPLETE_RUN_TDD_PROMPTING_TECHNIQUES.md - planning/planning_output.md - feasibility/feasibility_analysis.md - design/design_hld_lld.md - testing/testing_strategy.md - testing/test_use_cases.md - deployment/deployment_plan.md - project_brief.json RATIONALE: - These documents describe TDD tests for backend code (prompting techniques) - Backend code tests and their documentation belong in docs/backend/ - NOT docs/agent/ (which would be for agent system documentation itself) Updated all internal references to reflect new location: - docs/agent/* → docs/backend/* LESSON LEARNED: Always verify project structure conventions before creating new directories. Tests documentation should match the codebase type: - Backend tests → docs/backend/ - Frontend tests → docs/frontend/ - Infrastructure → docs/infrastructure/
Added comprehensive conventions document documenting: - LL-001: Verify structure before creating directories - LL-002: No numbered prefixes in filenames - Documentation location mapping (backend/frontend/infra) - Pre-documentation checklist - Quick reference tables This prevents future errors in documentation placement, specifically avoiding incorrect placement like docs/agent/ instead of docs/backend/.
Added comprehensive lesson learned about: - Architecture pattern: Generic Agent + Specialized Components + Domain Config - Integration of DocumentationValidatorAgent in SDLC pipeline - Automatic execution after each SDLC phase that generates docs - Domain-specific configuration (backend, frontend, infrastructure) - Prevention of errors: wrong location, emojis, numbers, structure This ensures documentation errors are caught immediately during generation, not discovered manually afterwards. Proposed: FEATURE-DOC-VALIDATOR-SDLC-001
Extended domain configuration to include: - infrastructure (docs/infraestructura/) - devops (docs/devops/) - operaciones (docs/operaciones/) - gobernanza (docs/gobernanza/) - ai (docs/ai/) - agents_definition (.github/agents/) Marked as DOCUMENTO VIVO (living document) - to be updated when new domains are added to the project. Updated quick reference mapping table with all domains.
Added comprehensive documentation organization: - Created docs/INDEX.md with navigation by roles (AI Engineers, Backend Devs, Frontend Devs, DevOps, SRE, Infrastructure, QA, PM, Governance) - Updated CONVENTIONS with multilevel structure: - Parent level (transversal): gobernanza, adr, analisis, vision, planificacion, guias, anexos - 8 autonomous domains: ai, backend, frontend, infraestructura, devops, operaciones, qa, dora - Each domain can have: gobernanza/, adr/, procedimientos/, testing/, README.md - Documented difference between Infraestructura (DESIGN/BUILD) and Operaciones (USE/MAINTAIN - SRE) - Added complete mapping of scripts/ to docs/ domains - Setup initial commands and useful aliases - Techniques and frameworks table (TDD, Constitutional AI, Auto-CoT, etc.) Structure version: 2.0.0 (Multilevel with autonomous domains)
Created contextual README for backend domain with: - SDLC documentation structure (planning, feasibility, design, testing, deployment) - Purpose and main content sections - Related code locations (scripts/coding/ai/, api/) - Getting started guides for AI Engineers, Backend Devs, and TDD implementers - Useful commands and conventions - Current status (2/11 test modules implemented, 18% complete) Provides clear entry point for backend domain documentation.
…nalysis Add complete DevOps domain documentation based on analysis of IACT's 100+ automation scripts: 1. New Analysis Document (analysis_tfg_server_vs_iact_scripts.md): - Comprehensive comparison of TFG-Server vs IACT scripts - Identified IACT strengths: 30+ AI agents, 100+ scripts, extensive validation - Identified critical gap: Release automation (Priority 1) - Quantitative analysis: IACT wins 9/11 categories - Adoption roadmap with 3 priority levels 2. Enhanced DevOps README (docs/devops/README.md): - 4-layer automation architecture (Git Hooks → CI/CD → Quality Gates → SDLC) - Documented 9 major script categories (100+ scripts total) - Complete guides for developers, DevOps engineers, and SREs - Shell and Python standards, CI/CD conventions - Integration with all 8 project domains - Roadmap and metrics of success 3. Updated Conventions (CONVENTIONS_AND_LESSONS_LEARNED.md): - Added LL-004: DevOps comparative analysis lesson - Documented gaps and adoption priorities - Added references to analysis and DevOps docs Key Findings: - IACT has superior automation compared to TFG-Server (9/11 categories) - Critical gap: Need release automation with semantic versioning - Recommended adoption: 3 priorities (Release, Constitution Evolution, Feature CLI) Scripts Documented: - CI/CD: 40+ scripts (ci-local.sh, quality gates, security, testing) - Git Hooks: 8+ hooks (secrets, naming, environment validation) - Validation: 20+ scripts (security, compliance, docs, quality) - Infrastructure: 30+ scripts (Cassandra, DR, load testing, logging, WASI) - AI Agents: 30+ agents (SDLC, automation, TDD) - Testing: 200+ tests with 80%+ coverage target - DORA Metrics: 4 metrics tracked Impact: - Complete visibility of DevOps automation landscape - Clear roadmap for future improvements - Best practices adoption from external projects - Maintains focus on IACT's unique strengths (AI agents) Closes: Analysis and documentation tasks for DevOps domain Relates to: LL-004 in CONVENTIONS_AND_LESSONS_LEARNED.md
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Pull Request Overview
This pull request provides comprehensive documentation for agents, conventions, and backend with TDD implementation for prompting techniques. The PR consolidates documentation, reorganizes the SDLC structure from docs/agent to docs/backend, and adds TDD tests for Auto-CoT and Self-Consistency techniques.
Key changes:
- Implementation of TDD tests for prompting techniques (Auto-CoT, Self-Consistency)
- Complete SDLC documentation (Planning, Feasibility, Design, Testing, Deployment)
- Reorganization of backend and DevOps documentation with multilevel structure
- Addition of comprehensive agent documentation in
.github/agents/
Reviewed Changes
Copilot reviewed 25 out of 29 changed files in this pull request and generated 13 comments.
Show a summary per file
| File | Description |
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scripts/run_sdlc_pipeline_for_tdd.py |
Pipeline script to execute full SDLC for TDD test generation |
scripts/coding/ai/tests/techniques/test_self_consistency.py |
TDD tests for Self-Consistency agent (305 lines, 20+ tests) |
scripts/coding/ai/tests/techniques/test_auto_cot_agent.py |
TDD tests for Auto-CoT agent (502 lines, 25+ tests) |
scripts/coding/ai/tests/conftest.py |
Shared pytest fixtures and configuration (15+ fixtures) |
docs/backend/ |
Complete SDLC documentation structure (planning, feasibility, design, testing, deployment) |
docs/devops/README.md |
Comprehensive DevOps documentation with automation architecture |
docs/devops/analysis_tfg_server_vs_iact_scripts.md |
Comparative analysis of TFG-Server vs IACT scripts |
docs/INDEX.md |
Main project documentation index with navigation by roles and domains |
.github/agents/ |
Comprehensive agent documentation (techniques, SDLC, LLM providers, domain agents, DevOps) |
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| def test_init_with_custom_config(self, self_consistency_config): | ||
| """Test: Inicialización con configuración personalizada.""" | ||
| agent = SelfConsistencyAgent(config=self_consistency_config) |
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| def test_init_with_different_num_samples(self, num_samples): | ||
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| """Test: Pipeline completo de Self-Consistency.""" | ||
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Aquí tienes el Pull Request redactado en formato técnico y profesional para este conjunto de cambios:
Título del PR
Documentación integral de agentes, convenciones y backend con TDD para técnicas de prompting
Descripción
Este Pull Request consolida la documentación de agentes y convenciones del proyecto, reorganiza la estructura de SDLC, y añade pruebas TDD para técnicas de prompting. Se incluyen mejoras en organización, documentación multilevel y guías de backend y DevOps.
Documentación de agentes
docs/agenthaciadocs/backendConvenciones y lecciones aprendidas
Estructura documental
Pruebas y TDD
Cambios realizados
Este PR cierra automáticamente los siguientes issues si se aprueba:
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