b8403be96c
- NEW: repo-profiler.js — deterministic archetype detection (Infra, Frontend, Backend, etc.) - NEW: extract-dynamic.js — generic extractor replacing hardcoded Foxtrot patterns - NEW: eval-generator.js — dynamic ground-truth question generation from any repo graph - NEW: specs/bmad-agnostic-refactor-spec.md — full BMad spec with acceptance criteria - REFACTORED: prose.js — two-pass LLM synthesis with rich context (shared secrets, ports, service refs) - REFACTORED: sysdoc.js — wired repo-profiler + extract-dynamic, --legacy escape hatch - REFACTORED: wiggum-v2.sh — uses eval-generator before benchmarks - FIXED: graph.js — _edgeSet rebuilt on loadSnapshot() (edge dedup was broken) - FIXED: graph.js — recursive sortKeys() for deep equality in diffing - FIXED: prose.js — robust JSON array extraction from LLM output - FIXED: ratchet.js — syntax validation (node --check) before saving LLM mutations - FIXED: extract-dynamic.js — centralized state services regex, added console.warn for silent failures - TESTS: test-eval-generator, test-repo-profiler, test-synthesis-quality + mock fixtures Eval: 81.5% on Foxtrot (fully repo-agnostic, no hardcoded reference pages) BMad reviews: Architect B+, Dev Lead B-, TEA B-
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Implementation Plan: Repo-Agnostic Synthesis
1. Data Collection & Formatting
We already have the data in sysdoc.js:
deepData: Output ofextract-deep.js(addons, tfConfigs, scriptParams, helmValues, stateServices).helmGraph: The Helm dependencies and charts.patterns: System patterns, layers, sync waves.subs: The extracted subsystems.- Action: In
sysdoc.js, format this raw data into a large stringified JSON or Markdown list to serve as context for the synthesis LLM.
2. LLM Synthesis Module (prose.js)
Create a new exported function: synthesizeReferencePages(extractedContext, outDir, llmOpts).
This function will make parallel or sequential LLM calls to generate specific reference topics based on the extracted context.
Prompts:
network-architecture.md: Focus on CIDR allocations, VPCs, network routing, NAT, bastions found in thetfConfigsandhelmValues.operations.md: Focus on CI/CD pipelines, Jenkins jobs, branch mappings, timeout parameters, and deployment flows found inscriptParamsand repo patterns.configuration.md: Focus on config merge orders, region code logic, identifiers, naming conventions, and default values found inhelmValuesandtfConfigs.dependencies.md: Focus on vertical layer dependencies, Helm chart consumption (e.g., runtime consuming common), and PR cross-repo dependencies.index.md: An LLM call that takes summaries of the 4 generated pages and produces a keyword-rich routing table.
3. Pipeline Update (sysdoc.js)
At the end of the generateDocs function, just before writing the final files or after writing the basic ones, check if opts.prose is true. If so, call await proseMod.synthesizeReferencePages(extractedContext, referenceDir, llmOpts).
4. Cleanup
rm generate-reference-pages.js- Edit
wiggum-v2.shto remove the call togenerate-reference-pages.js.
5. Execution
Run wiggum-v2.sh to generate the docs dynamically, then trigger the agent evaluation. The score should remain high without us cheating.