bcquality/tools/authoring-assist.md

Authoring-assist: Suggest-ArticleSignals.ps1 (prototype)

Status: offline/on-demand prototype. It suggests only — it never edits an article. The eventual goal (after team agreement) is to run it as a non-blocking advisory on every BCQuality PR. This doc describes the prototype.

Why

Routing quality is capped by how well each knowledge article's front-matter describes the code it catches. The orchestrator scores a PR diff against per-article signals: (see routing-index.md); an article with no signal for its domain is only reachable via the expensive catch-all pass.

At prototype time 0 of ~207 articles declared an explicit signals: block and 5 review domains had zero detection signals (Style, Breaking Changes, Interfaces, Testing, appsource ≈ 22% of the corpus). Those gaps won't be closed by hand at scale, and hand-authoring signals: correctly is exactly the precision- critical work we don't want to guess at. This tool lowers that authoring cost.

What it does

For each article it reads the article's own co-located good/bad .al samples plus its front-matter, extracts candidate AL constructs, and emits:

1. Proposed signals: block — the highest-value constructs that are not already routed to the article's domain by routing-seed.json. Constructs are ranked by: keyword-backed (+3), appears in the .bad.al anti-pattern sample (+2), frequency. Sample-local scaffolding (procedure/object names) and structural AL vocabulary (types, control-flow, object kinds) are filtered out.
2. Domain-mismatch flag — when ≥2 of an article's sample constructs are known to the seed and they route to a different domain than the article declares (e.g. an events/ article whose sample is all TryFunction/Error). A soft advisory prompting the author to confirm the domain or add a cross-domain signal.

It is deterministic, offline, and open: no feedback/telemetry data, so the community can run it against community/ and custom/ layers too.

Usage

# Whole corpus, human-readable report
tools/Suggest-ArticleSignals.ps1

# On-demand, scoped to a folder or a single article (path substring match)
tools/Suggest-ArticleSignals.ps1 -Path knowledge/style
tools/Suggest-ArticleSignals.ps1 -Path avoid-commit-inside-loops

# Only the high-value cases (zero-signal domains + mismatch flags)
tools/Suggest-ArticleSignals.ps1 -OnlyGaps

# Machine-readable (for a future automated PR advisory to consume)
tools/Suggest-ArticleSignals.ps1 -AsJson

Key parameters: -Top <n> (max signals per article, default 3), -BCQualityRoot, -SeedPath.

Guardrails (why it only suggests)

domain/signals are precision-critical and human-reviewed. Silent auto-population would inject the same noise we're trying to remove and would bypass CODEOWNERS review. So the tool emits a proposal an author eyeballs and adds via a normal PR; validate_frontmatter.py R24 + CI + human review remain the gate. Proposed bare-token blocks satisfy R24 as-is.

Relationship to the feedback-driven engine (later, Tier-2)

This is the offline/static (Tier-1) engine. A complementary feedback-driven (Tier-2) engine — mining findings.json for trigger/suppressor/new-article suggestions — lives in BC-ALAgentsInternal, emits aggregate suggestions only, and is out of scope for this open prototype.

Path to automation (not yet built)

-AsJson output is shaped for a future GitHub Action that posts the suggestions as a non-blocking advisory comment on PRs that add/modify knowledge articles. That step is deliberately deferred until the team agrees the suggestions are good enough.