aiwg
Version:
Deployment tool and support utility for AI context. Copies agents, skills, commands, rules, and behaviors into the paths each AI platform reads (Claude Code, Codex, Copilot, Cursor, Warp, OpenClaw, and 6 more) so one source of truth works across 10 platfo
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Markdown
kind: research
domain: SDLC artifacts
description: Validates SAD, ADRs, use cases, and NFRs against current architectural and engineering practice
detect:
glob:
- ".aiwg/architecture/*.md"
- ".aiwg/architecture/decisions/ADR-*.md"
- ".aiwg/requirements/UC-*.md"
- ".aiwg/requirements/NFR-*.md"
minCount: 1
focus_areas:
- architecture
- security
- performance
- api-design
- testing
- observability
- scalability
sources:
preferred:
- ietf
- w3c
- owasp
- cloud-vendor-docs
- conference-talks
- academic
exclude:
- seo-spam
- ai-content-farms
recency_default_months: 18
# SDLC Research Contributor
When the SDLC framework is in use (detected via the presence of architecture
documents, ADRs, use cases, or NFRs), `best-practices-audit` should weight
its research toward sources that have authority on architectural and
engineering decisions.
## What This Contributor Configures
### Focus Areas
The seven focus areas above represent the typical decision domains in
SDLC artifacts:
| Area | Typical artifact |
|------|------------------|
| `architecture` | SAD, component diagrams, deployment views |
| `security` | threat models, security gates, ADRs touching auth/encryption |
| `performance` | NFRs, performance test plans, capacity ADRs |
| `api-design` | OpenAPI/AsyncAPI specs, contract tests |
| `testing` | test strategy, master test plan, coverage reports |
| `observability` | tracing/logging/metrics ADRs |
| `scalability` | NFRs, load test reports, scaling ADRs |
When the user passes `--focus <area>`, the audit intersects that with this
list. If `--focus` is omitted, all seven are in scope.
### Source Preferences
**Preferred** (high-trust for SDLC):
- `ietf` — RFCs for protocols and interop
- `w3c` — web standards for frontends and APIs
- `owasp` — security best practices, ASVS, threat modeling
- `cloud-vendor-docs` — AWS/GCP/Azure/etc. architecture guides; vendor docs
are authoritative for their own services
- `conference-talks` — recorded sessions from peer-reviewed venues
(KubeCon, P99 Conf, RustConf, ...)
- `academic` — peer-reviewed papers when the topic is researchable
**Excluded**:
- `seo-spam` — content-farm articles optimized for search rather than
technical accuracy
- `ai-content-farms` — sites that auto-generate "tutorials" with hallucinated
code examples
### Recency Default
18 months. Architecture practice moves slowly enough that a 12-month window
loses important signal (e.g. recent practitioner consolidation), but a
36-month window pulls in advice that may be obsolete on fast-moving
substrates (CDK, GraphQL gateways, runtime updates).
For ADRs touching specific dependency versions, the audit should tighten
to 6–12 months automatically — but that's an audit-time decision, not a
contributor configuration.
## Anti-Pattern Reminders
- Do not collapse all SDLC research into one focus area. The audit's
per-area fan-out produces better signal-to-noise than one giant query.
- Do not include framework-specific sources here. If a project uses
React or Postgres, that's a `--framework` flag at audit time, not a
contributor configuration.
- Do not surface dissent by default — only when the user passes
`--dissent`. Surfacing dissent in every audit creates report noise.