rfc-app/docs/design/2026-06-06-configurable-collection-metadata.md

Solution Design: Configurable Collection Metadata (clean-doc tagging)

Author(s)	Ben Stull
Reviewers / approvers	Ben Stull
Status	draft
Version	v0.1.3
Source artifacts	Reference modeled: retired BDD Release Planner (wiggleverse/wiggleverse-ecomm-bdd-release-planner-app, RETIRED 2026-06-04) · Related: 2026-06-05-three-tier-projects-collections.md (§22) · Corpus: ecomm Shopify-modeled BDD (wiggleverse-ecomm-meta/research/shopify, ~1,238 scenarios) · Supersedes: 2026-06-06-per-type-surfaces.md

Change log

Date	Version	Change	By
2026-06-06	v0.1.0	Initial draft from discovery session OHM-0079.0	Ben Stull
2026-06-06	v0.1.1	Executive Summary → value-only; add §4 Pain Points; renumber per Solution Design template revision	Ben Stull
2026-06-06	v0.1.2	Reshuffle (Business Outcomes → §5); outcomes restated as business (adoption/diversity); Business Use Cases → solution-agnostic actor-goal scenarios	Ben Stull
2026-06-06	v0.1.3	Supersede the per-type-surfaces draft (harvest validation seam, malformed flag, unknown-field-rides-along, engine-unchanged, N=1 backcompat; bdd coverage kept as a future surface; §22.4a amendment work item); split personas into Business Actors (§6) + Product Personas (§10)	Ben Stull

---

1. Executive Summary

A deployment's corpus is only as valuable as the ability of the people running it to prioritise it, navigate it, and act on it — and as valuable as the downstream tools that can read structured signal out of it. Today that value is stranded: operators and contributors can't rank what matters or find content by what matters, and the tools meant to plan and build from the corpus have nothing structured to consume. This design delivers, for those people, the ability to rank what matters, find content by what matters, and hand clean machine-readable signal to the collaborators and tools that depend on it — turning a flat thousand-item corpus into something a team can actually plan and a downstream planner can build on, while keeping the source documents clean and readable. The outcome for the customer: lower-friction corpus planning for operators and contributors, broader adoption by teams whose document types rfc-app couldn't previously serve, and a corpus external tooling can consume without bespoke glue. (Value summary; scope and mechanism begin at §7.)

2. Business Context

The framework hosts RFC standardization for multiple deployments. One deployment hosts the ecomm BDD corpus — ~1,238 Shopify-modeled scenarios, one markdown file per scenario, slugged by feature ID (DD-FF-NNNN-slug). A standalone BDD Release Planner previously let operators search that corpus, attach metadata (priority P0–P3, owner, status), cluster scenarios into named releases, and emit each release as a roadmap phase. §22 (three-tier projects/collections) absorbed the planner's corpus hosting into rfc-app (the corpus now runs as a bdd project on the RFC deployment) and the planner was retired — but its annotation half (priority/tags on scenarios, filtering, bulk assignment) was never rebuilt. Operators planning work, and downstream tools consuming the corpus, currently have no structured, framework-native way to set or read that metadata. More broadly, teams evaluating rfc-app for other document types often need structured attributes (a priority, a status, domain tags) the platform can't yet express — so they go elsewhere.

3. Problem Statement

rfc-app cannot express or surface structured signal about its content. Tags are free-form strings with no filtering; there is no notion of priority or any other collection-defined attribute; the catalog is a flat list; and what little metadata exists is mixed into the top of every document. As a result, a corpus cannot be prioritised, navigated by attribute, planned in bulk, or cleanly consumed by downstream tools — and teams whose workflows depend on such attributes cannot adopt the platform at all.

4. Pain Points

#	Pain	Who feels it	Cost / frequency today
PP-1	Scenarios carry no priority, so triage and planning happen off-platform, in spreadsheets and memory	Release planner, contributor	Every planning cycle; signal lives off-platform and goes stale
PP-2	The catalog is a flat, unfilterable list — at ~1,200 scenarios, "show me the P0 checkout scenarios" is impractical	Reader, release planner	Every browse/triage; finding the right work is slow and error-prone
PP-3	Tags are free-form with no filtering payoff, so they're decorative and go unmaintained	Contributor	Ongoing; the one existing affordance rots
PP-4	Annotating many scenarios means opening many PRs, so bulk planning has no home in the tool	Release planner	Every batch; the core planning gesture is effectively impossible
PP-5	rfc-app metadata clutters the top of every document, hurting readability and making the corpus awkward to consume cleanly	Reader, downstream consumer	Every read; every downstream integration
PP-6	Downstream tools have no structured signal to read — the retired planner's capability left a gap	Downstream consumer	Continuous since the planner's retirement
PP-7	Teams whose document types need structured attributes can't model them, so they don't adopt rfc-app	Prospective adopter (org/team)	Every evaluation that ends in "not yet"

5. Targeted Business Outcomes

Business outcomes for rfc-app as a platform — adoption, reach, and diversity of use — not solution outputs. (Whether documents carry a priority is a solution output, tracked as a slice's Definition of Done in §14, not here.) These are the business change we expect once the pains in §4 are relieved.

Outcome	Success metric	Baseline → Target	Guardrail (must not regress)	How / when measured
Teams blocked by missing structured attributes now adopt rfc-app	# organizations on rfc-app; # active users	internal deployments only → external orgs onboard	existing deployments don't churn	deployment registry + usage analytics; quarterly
The platform hosts a wider variety of workflows and document types	# distinct document/collection types & field schemas in use; # distinct workflow patterns	today's handful (philosophy RFCs, BDD corpus) → broader mix	existing types' experience unchanged	type/schema census across deployments; quarterly
Corpus planning happens on-platform rather than in side tools	share of prioritisation/planning done in rfc-app vs spreadsheets	largely off-platform → on-platform	—	operator interviews + usage signals; quarterly

6. Business Actors / Roles

Real-world roles, solution-agnostic — they exist whether or not rfc-app does. The Business Use Cases (§9) are about these roles; the Product Personas (§10) map onto them.

Role	Responsible for (in the business)
Standards owner	Owns an organization's RFC / standards / requirements process; decides what's tracked and how
Release planner	Decides what work belongs in upcoming releases
Requirements author	Proposes and curates the requirements (e.g. BDD scenarios)
Requirements consumer	A person or downstream tool that plans or builds from the requirements
Reader	Anyone navigating the corpus to find what's relevant to them

7. Scope

• In scope: per-collection field schema in .collection.yaml (enum, tags, text); per-entry sidecar (<slug>.meta.yaml) as source of truth with pure-prose doc bodies; central schema validation (advisory at read, enforced at write); a "malformed metadata" catalog flag; schema-derived faceted left-pane filtering with counts; schema-derived metadata form (detail panel); single + bulk tag/untag with direct commit for authorized roles; dual-read compatibility + a one-shot frontmatter→sidecar migration tool + lazy migration on write; an amendment to the binding SPEC.md §22.4a contract (see §14 SLICE-0).
• Out of scope: release ordering, ship status, roadmap emission, RELEASE-PLAN.md generation, and the specification release-planning surface — all downstream, consuming sidecars from git. In-app management of field definitions / controlled vocabularies; corpus-wide tag rename/merge/delete. Sub-document grain. A whole-corpus metadata export endpoint.
• Future (recorded, not v1): a bdd coverage surface — a verifies-style ref field type plus a read-derived view mapping features to the spec sections they exercise and flagging gaps (harvested from the superseded per-type-surfaces draft, Part B.2). Built on the generic field machinery; deferred pending product questions (§16 Q4).
• Non-goals: rebuilding a bespoke "release" entity in rfc-app — releases are not modeled here at all; metadata is the only primitive. Hard-coding fields per collection type — schemas are collection-configured, not type-driven (D9).

8. Assumptions · Constraints · Dependencies

• Assumptions: git remains the content source of truth and downstream consumers can read the corpus from git; the BDD grain is one markdown file per scenario (already true for the ecomm corpus), so no sub-document parsing is needed.
• Constraints: rfc-app is a framework hosting multiple deployments — the upgrade must be mechanical and non-breaking, with §20 changelog/upgrade-steps; the hard secrets rule (§6.3) holds; metadata edits must respect scope-role authorization (§22 Part B / S3); the §22.4a "engine unchanged" rule holds (INV-8).
• Dependencies: the S3 scope-role resolver (auth.effective_scope_role); the existing git write-through path used by edit-meta (§9.5); the §22 collection model (.collection.yaml, cached_rfcs keyed by (collection_id, slug)); the binding SPEC.md §22.4a contract, which this design amends (SLICE-0).

9. Business Use Cases

Business use cases are solution-agnostic: they state what an actor (§6) wants to accomplish, why (value), and what success looks like — with no reference to rfc-app or any product. Each could in principle be satisfied by a person by hand (a concierge first pass) before any software. Form: "As a … I can … so that …" + a business-centric scenario.

BUC-1 — As a release planner, I can prioritise the requirements in a body of work, so that I can decide what belongs in upcoming releases.

Scenario: BUC-1 — Prioritise to plan releases
  Given a body of requirements of varying importance
  When the planner weighs which matter most
  Then they hold a ranking of those requirements by importance
  And can decide a release's contents from it

• Acceptance: the planner can select and justify the next release's contents from the relative importance of the work.

BUC-2 — As a planner facing a large body of requirements, I can organise and triage it within a normal working session, so that planning actually gets done rather than deferred or improvised.

Scenario: BUC-2 — Triage at scale
  Given more requirements than can be weighed one at a time
  When the planner ranks and groups them in bulk
  Then the body of work reflects those decisions without per-item drudgery

• Acceptance: a planner moves from an unsorted corpus to a prioritised plan in one sitting.

BUC-3 — As a team, I want the importance and categorisation of our requirements captured durably and shareably, so that other people and tools can plan from it without re-deriving it.

Scenario: BUC-3 — Durable, shareable signal
  Given requirements that have been weighed and categorised
  When someone or something else needs to plan from them
  Then they can read what matters and why without asking the original author

• Acceptance: a second party — person or tool — can pick up the work and plan from it unaided.

BUC-4 — As a team with a specialised body of documents, I can capture the attributes that make them actionable (importance, status, category), so that I can manage that work the way my domain requires.

Scenario: BUC-4 — Manage a domain's work on its own terms
  Given documents whose usefulness depends on domain-specific attributes
  When the team records and works with those attributes
  Then they can run their workflow with the distinctions it depends on

• Acceptance: the team can capture and act on the distinctions their domain requires — success is them choosing to manage the work this way.

BUC-5 — As someone consuming a large corpus, I can find the items that matter to my current purpose, so that I act on the right things instead of wading through everything.

Scenario: BUC-5 — Find what matters
  Given a large body of items
  When the consumer looks for the important ones for their task
  Then they can locate them quickly

• Acceptance: a person narrows a large corpus to the relevant, important subset for their task.

10. Product Personas

rfc-app's user types — each an embodiment of one or more Business Roles (§6). The Product Use Cases (§11) are about these personas.

Product persona	In rfc-app	Maps to business role(s)
Collection Owner	scope-role Owner on a collection/project; declares the collection's fields: schema (by editing .collection.yaml)	Standards owner
Contributor	scope-role contributor; sets metadata (single + bulk), proposes/curates entries	Requirements author; Release planner
Reader	viewer; browses and filters the catalog	Reader
Downstream consumer	an external system reading sidecars + .collection.yaml from git	Requirements consumer

11. Product Use Cases

Scenario: PUC-1 — Set priority/tags on a scenario (realizes BUC-1, BUC-4)
  Given I am a Contributor viewing a scenario whose collection defines priority and tags
  When I choose P0 in the priority control and add the tag "checkout"
  Then the metadata panel reflects P0 and the checkout tag
  And the change is committed directly to the scenario's sidecar

Scenario: PUC-2 — Bulk tag/untag from the catalog (realizes BUC-2)
  Given I have multi-selected several scenarios in the catalog
  When I choose "Set priority → P1" from the bulk action bar
  Then every selected scenario shows P1
  And the bulk change is one commit

Scenario: PUC-3 — Filter the catalog by facet (realizes BUC-5, BUC-1)
  Given the left pane shows faceted filters generated from the collection schema
  When I check Priority P0 and tag "checkout"
  Then the catalog shows only scenarios matching both
  And each facet value shows its result count

Scenario: PUC-4 — A Collection Owner declares fields (realizes BUC-4)
  Given a Collection Owner edits .collection.yaml to add a priority enum field
  When the collection is re-ingested
  Then the priority filter and the priority form control appear automatically

Scenario: PUC-5 — Migrate a collection to clean docs (product-only; enables BUC-3)
  Given a collection whose docs still carry top-of-doc frontmatter
  When the operator runs the frontmatter→sidecar migration
  Then each doc body becomes pure prose and a sidecar holds its metadata
  And rfc-app reads the collection identically before and after

Scenario: PUC-6 — A malformed entry is visibly fixable (realizes BUC-3)
  Given a stored entry whose metadata fails its collection's schema
  When the catalog renders
  Then the entry still loads (read never hard-fails)
  And it is flagged "malformed metadata" so a Contributor can fix it

12. UX Layout

12.1 Screen: Catalog (left pane) (serves PUC-3, PUC-6)

• Purpose: browse and filter a collection's entries.
• Layout (top → bottom): full-text search (existing); faceted filter groups (one per schema field + state): each a collapsible group with per-value result counts and multi-select checkboxes; tags-type fields include a "filter values…" search box to stay usable at 30+ values. (Chosen: faceted groups with counts — validated in brainstorming over flat chips.)
• States: happy: facets with counts · empty: "no entries match these filters" + clear-filters · loading: skeleton facets · error: retry · malformed: entries failing their schema carry a fixable "malformed metadata" marker (parallel to the §22.4c unreviewed flag), and are filterable.

12.2 Screen: Scenario detail — metadata panel (serves PUC-1)

• Purpose: view/edit one entry's metadata.
• Layout: one control per schema field — enum → single-select; tags → removable chips + add-tag input (with existing AI suggest where applicable); text → text input. The document body renders below as pure prose; metadata never appears inline.
• States: read (no edit role) shows values, no controls · edit (authorized) shows controls · saving: inline spinner · error: field-level validation message (e.g. "P5 is not an allowed priority").

12.3 Screen: Catalog — bulk action bar (serves PUC-2)

• Purpose: apply a field value to many entries at once.
• Layout: selecting ≥1 row reveals a sticky bar: "N selected · Set priority ▾ · Add tag ▾ · Remove tag ▾ · Clear". Each action targets one field; applying commits once.
• States: none selected: hidden · applying: progress · partial failure: toast naming entries that failed validation, others applied.

13. Technical Design

13.1 Invariants

• INV-1: The sidecar (<slug>.meta.yaml) is the source of truth for entry metadata; cached_rfcs is a derived index, fully rebuildable from git.
• INV-2: A document body (.md) never contains rfc-app metadata once migrated; metadata lives only in the sidecar.
• INV-3: Reading a collection never hard-fails on bad metadata — an invalid value against the schema surfaces as a warning, the entry still loads, and the catalog flags it (§12.1).
• INV-4: Metadata writes are authorized by scope-role (contributor+ on the collection) and validated at the write boundary; content-body edits keep their existing PR-review path.
• INV-5: A collection with no fields: block behaves exactly as today (free-form tags only). The §22.13 generated default collection is document with no fields → N=1 deployments see zero change (the load-bearing backcompat guarantee).
• INV-6: Dual-read holds throughout: parser reads the sidecar if present, else legacy top-of-doc frontmatter, with identical resulting in-memory records.
• INV-7: Unknown / forward-compat keys in a sidecar ride along untouched — never dropped on read or rewrite, and never reported as malformed.
• INV-8: Engine unchanged (§22.4a) — this feature is additive and read-mostly; it never forks the content write path, the propose→branch→PR→graduate lifecycle, threads/flags/chat, or the storage model. Metadata edits reuse the existing edit-meta git write-through.

13.2 High-level architecture

flowchart LR
  subgraph Git[content repo]
    CY[.collection.yaml<br/>fields: schema]
    MD[slug.md<br/>prose body]
    SC[slug.meta.yaml<br/>values]
  end
  CY --> ING[ingest / parser<br/>lenient, type-agnostic]
  MD --> ING
  SC --> ING
  ING --> VAL[metadata_schema.validate<br/>advisory at read]
  VAL --> DB[(cached_rfcs<br/>values + facet counts + malformed flag)]
  DB --> API[API: schema · list+filter · facets · edit]
  API --> FILT[left-pane faceted filters]
  API --> PANEL[detail metadata panel]
  API --> BULK[bulk select bar]
  PANEL -->|validate + direct commit| SC
  BULK -->|validate + 1 commit| SC
  SC -.read from git.-> CONS[downstream consumers]

• ingest/parser — reads .collection.yaml schema + sidecars (or legacy frontmatter), stays lenient and type-agnostic (unknown keys ride along, INV-7); rebuilds cached_rfcs; never authoritative.
• metadata_schema.validate(values, fields) → [problems] — the one place that knows a collection's required/forbidden fields and each field's shape (the seam harvested from the per-type-surfaces draft, modeled on registry.py). Advisory at ingest (warn + malformed flag, INV-3); enforced at the write boundary (single/bulk edit, INV-4).
• API — serves the schema, filtered lists with facet counts + malformed flag, and metadata edits; never writes metadata anywhere but the sidecar in git.

13.3 Data model & ownership

Entity	Owned by	Key fields	System of record
Collection field schema	Collection Owner	fields: {name → {type, values?, label}} in .collection.yaml	git
Entry metadata values	Contributor	sidecar <slug>.meta.yaml: lifecycle (slug,title,state,owners,…) + schema fields (priority,tags,…) + any forward-compat keys (INV-7)	git (sidecar)
Derived index	ingest	per-entry values + facet aggregations + malformed flag	cached_rfcs (SQLite, derived)

Field types (v1): enum (single-select; controlled by required values:), tags (multi-value; free-form unless values: given), text (free string). Future: ref (a typed cross-entry link, the basis for the deferred bdd verifies/coverage surface — §7 Future, §16 Q4). Unknown types are ignored with a warning (forward-compat).

Sidecar example:

slug: 01-01-0001-view-today-s-key-performance-metrics-at-a-glance
title: View today's key performance metrics at a glance
state: active
owners: [ben.stull]
priority: P1
tags: [dashboard, analytics]
owner: hasan

13.4 Interfaces & contracts

• GET /api/projects/<p>/collections/<c> — out: collection incl. fields schema. Errors: 404.
• GET /api/projects/<p>/collections/<c>/rfcs — in: filter params (?priority=P0&tags=checkout&state=active; repeatable → OR within a field, AND across fields; ?malformed=true) · out: entries with values + per-entry malformed flag + facets: {field → {value → count}}. Errors: 400 on unknown field.
• POST /api/projects/<p>/collections/<c>/rfcs/<slug>/meta — in: {field: value, …} · effect: metadata_schema.validate → write sidecar → commit directly → re-ingest. Errors: 403 (role), 422 (invalid value).
• POST /api/projects/<p>/collections/<c>/meta/bulk — in: {slugs, op: set|add|remove, field, value} · out: {applied, rejected:[{slug,reason}]} · effect: validate → write N sidecars → one commit → re-ingest. Errors: 403, 422.

13.5 Per–Product-Use-Case design

PUC-2 — Bulk tag/untag

sequenceDiagram
  actor U as Contributor
  participant C as Catalog UI
  participant A as API
  participant V as metadata_schema
  participant G as Git
  participant D as cached_rfcs
  U->>C: select rows, "Set priority P1"
  C->>A: POST /meta/bulk {slugs, set, priority, P1}
  A->>A: authz (scope-role)
  A->>V: validate values vs schema
  A->>G: write N sidecars, 1 commit
  A->>D: re-ingest affected entries
  A-->>C: {applied, rejected}
  C-->>U: rows show P1; toast on any rejected

• Implementation: reuse the edit-meta git write-through, extended to target the sidecar and batch N files into one commit. Honors INV-1/INV-4/INV-8.

PUC-5 — Migration

• Implementation: a tool (framework CLI verb / tools/ script) walks a collection; for each entry with legacy frontmatter it writes <slug>.meta.yaml and rewrites <slug>.md to the body only — one commit per collection, idempotent, preserving unknown keys (INV-7). Dual-read (INV-6) means it can run anytime; lazy migration converts stragglers on first metadata edit.

13.6 Non-functional requirements & cross-cutting concerns

• Security & privacy: edits gated by auth.effective_scope_role; no secrets in sidecars; git history records authorship.
• Performance & scale: facet counts computed from the derived DB; responsive at ~1.2k entries with dozens of tag values (indexed value columns / aggregation).
• Availability & resilience: bad metadata never blocks read (INV-3); a failed re-ingest leaves git authoritative, recoverable by full rebuild.
• Observability: log each metadata commit (actor, field, entry count); warn-log + count schema-validation failures on ingest.
• Accessibility: facet groups and form controls keyboard-navigable; checkboxes labelled value + count.

13.7 Key decisions & alternatives considered

Decision	Chosen	Alternatives	Why
Release modeling	Metadata only; releases downstream	First-class release entity; release-typed tags with behavior	Operator pulled ordering/ship-status out of rfc-app
Tag system shape	One generic typed-field system (Approach A)	Releases first-class + simple tags; namespaced facets	Tags/priority/custom are all just fields
Schema model (D9)	Pure collection-config	Type-driven hard-coded schemas (per-type-surfaces draft)	Flexible, data-driven; a type shouldn't fix the fields
Metadata storage	Sidecar per entry	Frontmatter (today + per-type-surfaces draft); end-of-doc; index file; DB-only	Clean docs + git-visible + per-entry locality
Left-pane filtering	Faceted groups with counts	Flat facet chips	Scales to the ~1.2k-scenario, many-tag corpus
Edit governance	Direct commit for authorized roles (bulk = 1 commit)	PR per change	Bulk planning impractical via PR-per-toggle
bdd coverage (D10)	Future per-type surface over a ref field	Build now; drop entirely	Valuable but not v1; needs product questions (Q4)

13.8 Testing strategy

Unit: schema parsing (all types, missing block); sidecar round-trip incl. unknown-key preservation (INV-7); dual-read equivalence (INV-6); validation (reject bad enum, accept free-form tag); malformed-flag derivation; facet aggregation; bulk op (set/add/remove, single commit, partial-rejection). Two-tier local-Docker→PPE for API + git write-through. "Tested" = the PUC acceptance scenarios pass + migration proven idempotent and reversible-on-read.

13.9 Failure modes, rollback & flags

• Invalid value committed out-of-band → ingest warns + loads with the value flagged malformed (INV-3).
• Re-ingest fails after commit → git authoritative; full rebuild recovers.
• Migration rollback: dual-read keeps an un-/partly-migrated corpus working; the migration commit is revertible.
• Feature flag: inherently opt-in per collection (INV-5) — no global flag; absent a fields: block, behavior is unchanged.

14. Delivery Plan

14.1 Approach / strategy

Amend the binding contract first, then build storage/compat, then schema, then read, then write. Each build slice is shippable and non-breaking.

14.2 Slicing plan

SLICE-0 — Amend SPEC.md §22.4a (contract) → unblocks the rest

• Depends on: —
• Definition of done: §22.4a reframed — item 1 (entry schema) is collection-configured sidecar fields, not type-driven frontmatter; item 3 (type surfaces) deferred to a future design (bdd coverage recorded); the per-type-surfaces draft marked superseded; §20 changelog entry. Doc-only; no code.

SLICE-1 — Sidecar storage + dual-read + migration → completes PUC-5, PUC-6

• Depends on: SLICE-0
• DoD: parser reads sidecar-else-legacy (INV-6), preserves unknown keys (INV-7); migration tool idempotent; existing collections load byte-identically; malformed flag derived; tests green.

SLICE-2 — Collection field schema + central validation → completes PUC-4

• Depends on: SLICE-1
• DoD: .collection.yaml fields: parsed; metadata_schema.validate advisory at read / enforced at write; schema served via the collection API; no-fields: collections unchanged (INV-5).

SLICE-3 — Faceted left-pane filtering (read) → completes PUC-3

• Depends on: SLICE-2
• DoD: list endpoint returns facet counts + honors filter params (incl. malformed); left pane renders faceted groups with counts + tag-value search; filters compose (AND across fields).

SLICE-4 — Single-entry metadata edit → completes PUC-1

• Depends on: SLICE-2
• DoD: detail panel renders schema controls; POST …/meta validates, direct-commits, re-ingests; scope-role gated (INV-4); lazy-migrates a legacy entry on first edit.

SLICE-5 — Bulk tag/untag → completes PUC-2

• Depends on: SLICE-3, SLICE-4
• DoD: multi-select + bulk bar; POST …/meta/bulk applies set/add/remove as one commit; partial-rejection reported.

14.3 Rollout / launch plan

Pre-v1, single production: ship slices in order to the RFC deployment; each minor bump carries §20 changelog + upgrade steps. Opt-in per collection (INV-5): a deployment adopts it only by declaring a fields: block and (optionally) running the migration.

14.4 Risks & mitigations

Risk	L/I	Mitigation
Amending binding §22.4a destabilises a shipped contract	M/M	SLICE-0 doc-only, reviewed; dual-read keeps runtime non-breaking; supersede note preserves rationale
Frontmatter→sidecar migration corrupts content	L/H	Dual-read; idempotent, revertible migration; body-byte-identity + unknown-key tests
Doubling file count (sidecars) clutters corpus	M/L	Docs stay clean; sidecars small/co-located
Direct-commit metadata edits bypass review	M/M	Scope-role gate (INV-4); content-body edits still PR'd; git audit trail
Facet aggregation slow at scale	L/M	Compute from indexed derived DB; measure at ~1.2k entries

15. Traceability matrix

Pain	Business UC	Product UC	Slice	Tests
— (contract)	—	—	SLICE-0	(doc review)
PP-5	BUC-3	PUC-5, PUC-6	SLICE-1	test_dual_read_equiv, test_migration_idempotent, test_unknown_keys_preserved
PP-7	BUC-4	PUC-4	SLICE-2	test_schema_parse, test_validate
PP-2	BUC-5, BUC-1	PUC-3	SLICE-3	test_facet_counts, test_filter_compose
PP-1, PP-3	BUC-1, BUC-4	PUC-1	SLICE-4	test_single_meta_commit, test_authz
PP-4	BUC-2	PUC-2	SLICE-5	test_bulk_one_commit, test_partial_reject
PP-6	BUC-3	(consumer reads git)	—	test_sidecar_schema_stable

16. Open Questions & Decisions log

Open

#	Question	Owner	Blocks
Q1	Do downstream consumers read sidecars from git, via API, or both? (leaning git)	Ben	nothing v1
Q2	Ship multi-enum (multi-select controlled) in v1 or later?	Ben	SLICE-2 scope
Q3	Exact §22.4a amendment wording + the future-surfaces home	Ben	SLICE-0
Q4	bdd coverage: ref field grammar + does a coverage view honor §22's no-cross-collection-join rule as hyperlinks?	Ben	future surface

Resolved

#	Decision	Resolution	Date
D1	Release behaviors	Out of rfc-app; downstream	2026-06-06
D2	Tag system shape	Approach A — one generic typed-field system	2026-06-06
D3	Metadata grain	Per entry (corpus already one file per scenario)	2026-06-06
D4	Schema location	.collection.yaml fields: block	2026-06-06
D5	Value storage	Sidecar <slug>.meta.yaml; doc body pure prose	2026-06-06
D6	Left-pane filtering	Faceted groups with counts	2026-06-06
D7	Edit governance	Direct commit for authorized roles; bulk = 1 commit	2026-06-06
D8	Management scope	Deferred; edit .collection.yaml in git for v1	2026-06-06
D9	Schema model	Pure collection-config; not type-driven (supersedes per-type-surfaces)	2026-06-06
D10	bdd coverage	Keep as a future per-type surface over a ref field; not v1	2026-06-06
D11	per-type-surfaces draft	Superseded by this spec; §22.4a to be amended (SLICE-0)	2026-06-06

17. Glossary & References

• Sidecar — <slug>.meta.yaml, the per-entry metadata file that is the source of truth; keeps the .md body pure prose.
• Field schema — the fields: block in .collection.yaml declaring a collection's typed metadata fields.
• Facet — a schema field surfaced as a left-pane filter group with per-value counts.
• Malformed metadata — stored values that fail their collection's schema; flagged in the catalog, never a hard read failure (INV-3).
• Downstream consumer — an external tool (e.g. a release planner) that reads corpus metadata from git; rfc-app does not model releases.
• References: retired BDD Release Planner; superseded per-type-surfaces draft (2026-06-06-per-type-surfaces.md); §22 three-tier design; SPEC.md §7.1 (left-pane filter), §9.5 (edit-meta), §20 (versioning), §22.4a (per-type contract — to be amended), §22 Part B / S3 (scope-role).