Les enseignants ont besoin de moyennes à jour immédiatement après la publication ou modification des notes, sans attendre un batch nocturne. Le système recalcule via Domain Events synchrones : statistiques d'évaluation (min/max/moyenne/médiane), moyennes matières pondérées (normalisation /20), et moyenne générale par élève. Les résultats sont stockés dans des tables dénormalisées avec cache Redis (TTL 5 min). Trois endpoints API exposent les données avec contrôle d'accès par rôle. Une commande console permet le backfill des données historiques au déploiement.
139 lines
3.7 KiB
Markdown
139 lines
3.7 KiB
Markdown
---
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name: 'step-01-load-context'
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description: 'Load NFR requirements, evidence sources, and knowledge base'
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nextStepFile: './step-02-define-thresholds.md'
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knowledgeIndex: '{project-root}/_bmad/tea/agents/bmad-tea/resources/tea-index.csv'
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outputFile: '{test_artifacts}/nfr-assessment.md'
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---
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# Step 1: Load Context & Knowledge Base
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## STEP GOAL
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Gather NFR requirements, evidence sources, and knowledge fragments needed for assessment.
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## MANDATORY EXECUTION RULES
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- 📖 Read the entire step file before acting
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- ✅ Speak in `{communication_language}`
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- 🚫 Halt if implementation or evidence is unavailable
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---
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## EXECUTION PROTOCOLS:
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- 🎯 Follow the MANDATORY SEQUENCE exactly
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- 💾 Record outputs before proceeding
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- 📖 Load the next step only when instructed
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## CONTEXT BOUNDARIES:
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- Available context: config, loaded artifacts, and knowledge fragments
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- Focus: this step's goal only
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- Limits: do not execute future steps
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- Dependencies: prior steps' outputs (if any)
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## MANDATORY SEQUENCE
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**CRITICAL:** Follow this sequence exactly. Do not skip, reorder, or improvise.
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## 1. Prerequisites
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- Implementation accessible for evaluation
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- Evidence sources available (test results, metrics, logs)
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If missing: **HALT** and request the missing inputs.
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---
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## 2. Load Configuration
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From `{config_source}`:
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- Read `tea_browser_automation`
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---
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### Tiered Knowledge Loading
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Load fragments based on their `tier` classification in `tea-index.csv`:
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1. **Core tier** (always load): Foundational fragments required for this workflow
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2. **Extended tier** (load on-demand): Load when deeper analysis is needed or when the user's context requires it
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3. **Specialized tier** (load only when relevant): Load only when the specific use case matches (e.g., contract-testing only for microservices, email-auth only for email flows)
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> **Context Efficiency**: Loading only core fragments reduces context usage by 40-50% compared to loading all fragments.
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## 3. Load Knowledge Base Fragments
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From `{knowledgeIndex}` load:
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- `adr-quality-readiness-checklist.md`
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- `ci-burn-in.md`
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- `test-quality.md`
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- `playwright-config.md`
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- `error-handling.md`
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**Playwright CLI (if `tea_browser_automation` is "cli" or "auto"):**
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- `playwright-cli.md`
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**MCP Patterns (if `tea_browser_automation` is "mcp" or "auto"):**
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- (existing MCP-related fragments, if any are added in future)
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---
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## 4. Load Artifacts
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If available, read:
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- `tech-spec.md` (primary NFRs)
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- `PRD.md` (product-level NFRs)
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- `story` or `test-design` docs (feature-level NFRs)
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---
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## 5. Confirm Inputs
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Summarize loaded NFR sources and evidence availability.
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---
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## 6. Save Progress
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**Save this step's accumulated work to `{outputFile}`.**
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- **If `{outputFile}` does not exist** (first save), create it using the workflow template (if available) with YAML frontmatter:
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```yaml
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---
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stepsCompleted: ['step-01-load-context']
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lastStep: 'step-01-load-context'
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lastSaved: '{date}'
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---
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```
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Then write this step's output below the frontmatter.
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- **If `{outputFile}` already exists**, update:
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- Add `'step-01-load-context'` to `stepsCompleted` array (only if not already present)
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- Set `lastStep: 'step-01-load-context'`
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- Set `lastSaved: '{date}'`
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- Append this step's output to the appropriate section of the document.
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**Update `inputDocuments`**: Set `inputDocuments` in the output template frontmatter to the list of artifact paths loaded in this step (e.g., knowledge fragments, test design documents, configuration files).
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Load next step: `{nextStepFile}`
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## 🚨 SYSTEM SUCCESS/FAILURE METRICS:
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### ✅ SUCCESS:
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- Step completed in full with required outputs
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### ❌ SYSTEM FAILURE:
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- Skipped sequence steps or missing outputs
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**Master Rule:** Skipping steps is FORBIDDEN.
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