Deploying the three-tier series onto OHM crash-looped on migration 029:
`NOT NULL constraint failed: cached_branches__new.collection_id`, then a UNIQUE
collision. Root cause: the v0.39.0 default→ohm re-stamp updated
cached_rfcs.project_id but NOT the entry-satellite tables, so ~1.3k
cached_branches rows were stranded at project_id='default' — which 029's
per-project collection backfill can't map (NULL), some of which also duplicate
freshly-re-mirrored 'ohm' rows (UNIQUE), and some of which reference entries
that no longer exist.
Fix — a repair prologue at the top of 029 (no schema change):
- drop stale rows that duplicate an already-correctly-stamped row (keep the
fresh copy) for the branch-keyed tables;
- re-derive each satellite's project_id from its entry (cached_rfcs, by slug);
- drop rows whose entry no longer exists (stale cache, rebuildable from gitea).
A no-op on clean/fresh deployments (empty or consistent satellites).
Validated against a snapshot of the live OHM DB: 029→032 apply cleanly, zero
NULL collection_id, FK check clean, watches/RFCs/branch_visibility preserved,
cached_branches 1397 → 1291 (−67 no-RFC, −39 dups). Fresh-install path
unchanged: existing 029 suite green + a new regression test for the
stale/dup/orphan shape. Full backend suite 547 passed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- §1 Business Context holds the whole business lens (1.1–1.9), solution-agnostic
- §2 Solution Proposal introduces the chosen approach (and justifies build over
a manual alternative); may be non-software in general
- Renumber product/engineering lenses to §§3–7
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Executive Summary → value-only (no solution)
- New §4 Pain Points (PP-1..PP-7)
- Business Outcomes → §5, restated as business outcomes (adoption/diversity),
not solution outputs
- Business Use Cases rewritten as solution-agnostic actor-goal scenarios
- Renumber per the Solution Design template revision
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-06 07:15:35 -07:00
7 changed files with 400 additions and 165 deletions
| 2026-06-06 | v0.1.5 | Move Business Actors to §1.3 (define roles before Problem/Pain reference them) | Ben Stull |
| 2026-06-06 | v0.1.6 | §7.1 execution convention — each slice is its own writing-plans→executing-plans coding session, plans just-in-time | Ben Stull |
---
## 1. Executive Summary
## 1. Business Context
rfc-app gains a generic, **per-collection-configurable metadata system**. A collection declares its fields — `priority`, `tags`, and arbitrary custom fields — in its `.collection.yaml`; each entry's *values* live in a **sidecar** (`<slug>.meta.yaml`) so the document body stays pure prose. rfc-app renders schema-driven forms and **faceted left-pane filters**, and supports fast **single + bulk tag/untag** via direct commits for authorized roles. This restores the *corpus-annotation* capability of the retired BDD Release Planner inside the framework, while keeping release *planning* (ordering, ship status, roadmap emission) a downstream concern that reads the sidecars straight from git.
*The business lens — solution-agnostic throughout. No mechanism is proposed until §2.*
## 2. Business Context
### 1.1 Executive Summary
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.
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. The value at stake is **lower-friction corpus planning** for operators and contributors, **broader adoption** by teams whose document types the platform couldn't previously serve, and **a corpus external tooling can consume without bespoke glue**. *(Value summary; the solution is proposed in §2.)*
## 3. Problem Statement
### 1.2 Background
Today rfc-app metadata is weak and intrusive:
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. 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.
- **Tags are free-form strings** with **no filtering** — §7.1 specifies a `Tag:` filter chip that was never implemented.
- **No priority**, and no way for a collection to declare any other structured field.
- **No per-collection schema** — every collection gets the same fixed frontmatter shape; a `bdd` collection cannot say "scenarios have a P0–P3 priority."
- **Metadata pollutes the document body** — a large YAML frontmatter block sits at the top of every doc, mixing rfc-app lifecycle bookkeeping with content metadata.
- **No bulk workflow** — annotating hundreds of scenarios one PR at a time is impractical, so the planner's core gesture has no analog.
### 1.3 Business Actors / Roles
Result: corpus authors can't meaningfully prioritise/tag, downstream consumers have nothing structured to read, and documents aren't clean.
Real-world roles, **solution-agnostic** — they exist whether or not rfc-app does. They are defined here, before the Problem (§1.4) and Pain Points (§1.5) reference them; the Business Use Cases (§1.9) are about these roles, and the Product Personas (§3) map onto them.
## 4. Stakeholders / Personas / Actors
| 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 |
| Actor | Type | Goal in this design |
| --- | --- | --- |
| Corpus contributor | persona | Set priority and tags on a scenario when proposing/curating it |
| Release planner (operator) | persona | Bulk-prioritise/tag many scenarios quickly to shape a plan |
| Collection owner | operator | Declare the metadata fields a collection supports |
| Downstream consumer | system | Read structured per-scenario metadata from the git corpus (e.g. an external release planner) |
| Reader | persona | Read clean scenario docs; filter the catalog by priority/tag |
### 1.4 Problem Statement
## 5. Scope
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.
- **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; 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.
- **Out of scope:** release ordering, ship status, roadmap emission, `RELEASE-PLAN.md` generation — these stay downstream, consuming sidecars from git. In-app management of field definitions / controlled vocabularies; corpus-wide tag rename/merge/delete. Sub-document (per-scenario-within-a-file) grain. A whole-corpus metadata export endpoint.
- **Non-goals:** rebuilding a bespoke "release" entity in rfc-app — releases are not modeled here at all; metadata is the only primitive.
### 1.5 Pain Points
## 6. Assumptions · Constraints · Dependencies
| # | 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" |
- **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).
- **Dependencies:** the S3 scope-role resolver (`auth.effective_scope_role`) for edit authorization; 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)`).
### 1.6 Targeted Business Outcomes
## 7. 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 §7, not here.)
| Outcome | Success metric | Baseline → Target | Guardrail (must not regress) | How / when measured |
| --- | --- | --- | --- | --- |
| Authors can prioritise/tag scenarios | scenarios carrying a priority | 0 → corpus-wide | doc bodies stay prose-clean | corpus inspection after rollout |
| Corpus is filterable | left-pane facet filters available | none → priority+tags+state | filter latency acceptable at ~1.2k entries | manual + perf check |
| Downstream tools can consume metadata | sidecars readable from git | none → all migrated entries | sidecar schema stable | consumer integration |
| Clean docs | docs with no rfc-app frontmatter | 0% → 100% (post-migration) | dual-read keeps legacy working | post-migration inspection |
| 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 | today's handful → broader mix | existing types' experience unchanged | type/schema census; 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 |
## 8. Business Use Cases
### 1.7 Scope (business)
- **In scope:** the corpus can carry per-item importance and categorisation; people can find items by those attributes; the signal is captured durably and is consumable by other people and tools; teams with new document types can express the attributes their workflow needs.
- **Out of scope (business):** deciding *what* a given deployment's priorities or categories should be (that's the deployment's editorial choice); release sequencing and ship tracking as a business process (stays a downstream/operator concern).
- **Non-goals:** modelling "releases" as a first-class business object inside the platform.
*(Solution-specific scope/non-goals are in §2.)*
### 1.8 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).
- **Constraints:** rfc-app is a framework hosting multiple deployments — any change must be **mechanical and non-breaking**, with §20 changelog/upgrade-steps; the hard secrets rule (§6.3) holds; 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 used by `edit-meta` (§9.5); the §22 collection model; the binding `SPEC.md` §22.4a contract, which §2's solution amends (§7 SLICE-0).
### 1.9 Business Use Cases
Solution-agnostic: what an actor (§1.3) wants to accomplish, *why* (value), and what *success* looks like — **no reference to any product**. Each could be satisfied by a person by hand before any software. Form: "As a … I can … so that …".
**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.**
```gherkin
Scenario: BUC-1 — A contributor prioritises a scenario
Given abddcollectionwhoseschemadefinesapriorityfield
When acontributormarksascenarioasP0
Then thescenario'smetadatarecordspriorityP0
And thedocumentbodyisunchangedprose
Scenario: BUC-2 — A planner batch-prioritises a set of scenarios
Given acontributorhasselected40scenarios
When theysetpriorityP1ontheselection
Then all40carrypriorityP1
And thechangelandsasasingleauditablecommit
Scenario: BUC-3 — A downstream tool consumes priorities
Given scenarioscarrypriorityandtagsintheirsidecars
When anexternalreleaseplannerreadsthecorpusfromgit
Then itcangroupandorderscenariosusingthatmetadata
And rfc-appdidnotneedtomodelreleasesatall
Scenario: BUC-4 — Documents stay clean
Given amigratedcollection
When areaderopensascenariodocument
Then theyseeonlyprose,withnorfc-appmetadatablock
Scenario: BUC-1 — Prioritise to plan releases
Given abodyofrequirementsofvaryingimportance
When theplannerweighswhichmattermost
Then theyholdarankingofthoserequirementsbyimportance
And candecidearelease'scontentsfromit
```
- **Acceptance:** the planner can select and justify the next release's contents from the relative importance of the work.
-**BUC-1 acceptance:** the scenario's `priority` value is `P0` and its `.md` body is byte-identical to before.
- **BUC-3 acceptance:** sidecars + `.collection.yaml` are sufficient for a consumer to read priority/tags without rfc-app's API.
- **BUC-4 acceptance:** no `---` frontmatter remains in migrated docs.
**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.**
```gherkin
Scenario: BUC-2 — Triage at scale
Given morerequirementsthancanbeweighedoneatatime
When theplannerranksandgroupstheminbulk
Then thebodyofworkreflectsthosedecisionswithoutper-itemdrudgery
```
- **Acceptance:** a planner moves from an unsorted corpus to a prioritised plan in one sitting.
## 9. Product Use Cases
**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.**
```gherkin
Scenario: BUC-3 — Durable, shareable signal
Given requirementsthathavebeenweighedandcategorised
When someoneorsomethingelseneedstoplanfromthem
Then theycanreadwhatmattersandwhywithoutaskingtheoriginalauthor
```
- **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.**
```gherkin
Scenario: BUC-4 — Manage a domain's work on its own terms
Given documentswhoseusefulnessdependsondomain-specificattributes
When theteamrecordsandworkswiththoseattributes
Then theycanruntheirworkflowwiththedistinctionsitdependson
```
- **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.**
```gherkin
Scenario: BUC-5 — Find what matters
Given alargebodyofitems
When theconsumerlooksfortheimportantonesfortheirtask
Then theycanlocatethemquickly
```
- **Acceptance:** a person narrows a large corpus to the relevant, important subset for their task.
---
## 2. Solution Proposal
**The solution is to build it into rfc-app.** Give every collection a small, declared **field schema** (in its `.collection.yaml`) so it can carry structured metadata — priority, tags, and any custom fields the deployment defines. Store each entry's values in a **clean sidecar** file so the document body stays pure prose. rfc-app then **renders those fields as forms, filters the catalog by them (faceted, with counts), and lets authorized users tag in single and bulk gestures** committed straight to git; downstream tools read the values from the sidecars directly. It is one generic mechanism — tags and priority are just *fields* — not per-type special-casing and not a bespoke "release" entity.
**Why a software solution (and not a manual one).** A non-build alternative — operators maintaining priorities/tags in a shared spreadsheet — was considered and rejected: it leaves the corpus unfilterable in-tool (PP-2), keeps documents and the side-sheet out of sync, produces no durable git-readable signal for downstream tools (PP-5/PP-6), and does nothing for the adoption outcome (§1.6, PP-7). The value only lands if the structure lives with the content.
**Solution-specific scope.***Out:* release ordering, ship status, roadmap emission, the `specification` release-planning surface — all downstream, reading sidecars from git. In-app management of field definitions (edit `.collection.yaml` in git for v1); corpus-wide tag rename/merge/delete; sub-document grain; a whole-corpus 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 (harvested from the superseded per-type-surfaces draft); deferred pending §9 Q4. This solution **amends the binding `SPEC.md` §22.4a contract** (§7 SLICE-0).
*(The Product and Engineering sections below — §§3–7 — elaborate this build. They would be replaced by an operational plan if the chosen solution were non-software.)*
---
## 3. Product Personas
rfc-app's user types — each an embodiment of one or more Business Roles (§1.3). The Product Use Cases (§4) are about these personas.
| Product persona | In rfc-app | Maps to business role(s) |
- **Purpose:** browse and filter a collection's entries.
- **Layout (top → bottom):**
- **Search:** full-text box (existing).
- **Faceted filter groups** (one per schema field + state): each is a collapsible group showing per-value **result counts** and multi-select checkboxes; `tags`-type fields include a "filter values…" search box to stay usable at 30+ values. (Chosen layout: faceted groups with counts — validated in brainstorming over flat chips.)
- **States:** happy: facets with counts · empty: "no entries match these filters" with a clear-filters action · loading: skeleton facets · error: "couldn't load facets" with retry.
- **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.
- **States:** happy: facets with counts · empty: "no entries match" + clear-filters · loading: skeleton facets · error: retry · **malformed:** entries failing their schema carry a fixable marker (parallel to §22.4c `unreviewed`) and are filterable.
- **Layout:** a panel rendering 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 in the body.
- **States:** read (role without edit) shows values, no controls · edit (authorized) shows controls · saving: inline spinner · error: field-level validation message (e.g. "P5 is not an allowed priority").
- **Layout:** one control per schema field — `enum` → single-select; `tags` → removable chips + add-tag input (with existing AI suggest); `text` → text input. The body renders below as pure prose; metadata never appears inline.
### 10.3 Screen: Catalog — bulk action bar (serves PUC-2)
### 5.3 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 action bar: "*N* selected · Set priority ▾ · Add tag ▾ · Remove tag ▾ · Clear". Each action targets one field; applying commits once.
- **States:** none selected: bar hidden · applying: bar shows progress · partial failure: toast naming entries that failed validation, others applied.
- **Layout:** selecting ≥1 row reveals a sticky bar: "*N* selected · Set priority ▾ · Add tag ▾ · Remove tag ▾ · Clear". Applying commits once.
- **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 and the entry still loads.
- **INV-4:** Metadata writes are authorized by scope-role (contributor+ on the collection); 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 feature is additive and opt-in per collection.
- **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-3:** Reading a collection never hard-fails on bad metadata — an invalid value surfaces as a warning, the entry still loads, and the catalog flags it (§5.1).
- **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**.
- **INV-6:** Dual-read: 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, never reported as malformed.
- **INV-8:** **Engine unchanged** (§22.4a) — additive and read-mostly; 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.
### 11.2 High-level architecture
### 6.2 High-level architecture
```mermaid
flowchart LR
@@ -174,31 +242,33 @@ flowchart LR
MD[slug.md<br/>prose body]
SC[slug.meta.yaml<br/>values]
end
CY --> ING[ingest / parser<br/>validate vs schema]
ING --> DB[(cached_rfcs<br/>values + facet counts)]
ING --> VAL[metadata_schema.validate<br/>advisory at read]
VAL --> DB[(cached_rfcs<br/>values + facet counts + malformed)]
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 -->|direct commit| SC
BULK -->|1 commit| SC
PANEL -->|validate + direct commit| SC
BULK -->|validate + 1 commit| SC
SC -.read from git.-> CONS[downstream consumers]
```
- **ingest/parser** — owns reading`.collection.yaml` schema + sidecars (or legacy frontmatter), validating values, and rebuilding`cached_rfcs`; must never treat the DB as authoritative.
- **API** — owns serving the schema, filtered lists with facet counts, and metadata edits; must never write metadata anywhere but the sidecar in git.
- **`metadata_schema.validate(values, fields) → [problems]`** — the one place that knows a collection's required/forbidden fields and each field's shape (modeled on `registry.py`). Advisory at ingest (warn + malformed flag, INV-3); enforced at the write boundary (INV-4).
- **API** — serves the schema, filtered lists with facet counts + malformed flag, and metadata edits; never writes metadata anywhere but the sidecar.
### 11.3 Data model & ownership
### 6.3 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 |
- **Implementation:** reuse the `edit-meta` git write-through, extended to (a) target the sidecar rather than frontmatter and (b) batch N files into one commit. Honors INV-1/INV-4.
- **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, and for each entry with legacy frontmatter, writes `<slug>.meta.yaml` from the frontmatter and rewrites `<slug>.md` to the body only — one commit per collection, idempotent. Dual-read (INV-6) means this can run anytime; lazy migration converts stragglers on their first metadata edit.
- **Implementation:** a tool 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) lets it run anytime; lazy migration converts stragglers on first metadata edit.
- **Security & privacy:** metadata edits gated by `auth.effective_scope_role` (contributor+ on the collection); no secrets in sidecars; git history records authorship.
- **Performance & scale:** facet counts computed from the derived DB; must stay responsive at ~1.2k entries with dozens of tag values (indexed value columns / aggregation query).
- **Availability & resilience:** bad metadata never blocks read (INV-3); a failed re-ingest leaves git authoritative and is recoverable by full rebuild.
- **Observability:** log each metadata commit (actor, field, entry count); warn-log schemavalidation failures encountered on ingest.
- **Accessibility:** facet groups and form controls keyboard-navigable; checkboxes labelled with value + count.
- **Security & privacy:** edits gated by `auth.effective_scope_role`; no secrets in sidecars; git history records authorship.
- **Performance & scale:** facet counts from the derived DB; responsive at ~1.2k entries with dozens of tag values.
- **Availability & resilience:** bad metadata never blocks read (INV-3); failed re-ingest leaves git authoritative, recoverable by rebuild.
- **Observability:** log each metadata commit; warn-log + count schema-validation failures on ingest.
- **Accessibility:** facet groups and form controls keyboard-navigable; checkboxes labelled value + count.
### 11.7 Key decisions & alternatives considered
### 6.7 Key decisions & alternatives considered
| Decision | Chosen | Alternatives | Why |
| --- | --- | --- | --- |
| Release modeling | Metadata only; releases downstream | First-class release entity in rfc-app; release-typed tags with behavior | Operator pulled ordering/ship-status out of rfc-app; metadata is the only needed primitive |
| Tag system shape | One generic typed-field system (Approach A) | Releases first-class + simple tags; namespaced facets | Tags/priority/custom are all just fields; one mechanism |
| Metadata storage | Sidecar per entry | Top-of-doc frontmatter (today); end-of-doc block; collection index file; DB-only | Clean docs + git-visible to consumers + locality per scenario |
| Left-pane filtering | Faceted groups with counts | Flat facet chips | Scales to the ~1.2k-scenario, many-tag ecomm corpus |
| Edit governance | Direct commit for authorized roles (bulk = 1 commit) | PR per change | Bulk planning is impractical via PR-per-toggle |
| Mgmt UI | Deferred; edit `.collection.yaml` in git | In-app field/vocab management in v1 | Smallest coherent v1 |
| Solution type | Build into rfc-app | Manual (shared spreadsheet) | Manual leaves corpus unfilterable, out of sync, no git-readable signal (§2) |
| Release modeling | Metadata only; releases downstream | First-class release entity | Operator pulled ordering/ship-status out of rfc-app |
| Tag system shape | One generic typed-field system | 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 |
| Left-pane filtering | Faceted groups with counts | Flat facet chips | Scales to ~1.2k-scenario, many-tag corpus |
| Edit governance | Direct commit for authorized roles | PR per change | Bulk planning impractical via PR-per-toggle |
| bdd coverage (D10) | Future per-type surface over a `ref` field | Build now; drop | Valuable but not v1; needs Q4 |
### 11.8 Testing strategy
### 6.8 Testing strategy
Unit tests for: schema parsing (`fields:` block, all types, missing block); sidecar read/write round-trip; dual-read equivalence (frontmatter vs sidecar produce identical records); schema validation (reject bad enum, accept free-form tag); facet aggregation; bulk op (set/add/remove, single commit, partial-rejection). Two-tier local-Docker→PPE for the API + git write-through. "Tested" = the PUC acceptance scenarios pass plus the migration is proven idempotent and reversible-on-read.
- **Failure mode:** invalid value committed out-of-band → on ingest, warn + load entry with the raw value flagged (INV-3); not surfaced as a filter facet count error.
- **Failure mode:** re-ingest fails after commit → git is authoritative; full rebuild recovers.
- **Migration rollback:** dual-read means an un-migrated or partially-migrated corpus still works; the migration commit is revertible.
- **Feature flag:** the feature is inherently opt-in per collection (INV-5) — no global flag needed; absent a `fields:` block, behavior is unchanged.
- **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.
## 12. Delivery Plan
## 7. Delivery Plan
### 12.1 Approach / strategy
### 7.1 Approach / strategy
Build the storage/compat foundation first (sidecars + dual-read + migration) so nothing breaks, then the schema, then read (filtering), then write (single, bulk). Each slice is shippable and non-breaking.
Amend the binding contract first, then build storage/compat, then schema, then read, then write. Each build slice is shippable and non-breaking.
### 12.2 Slicing plan
**Execution convention.** Each slice is taken as **its own coding session** — `writing-plans → executing-plans → verify → ship/deploy → merge + version bump` — in dependency order, with the slice's implementation plan written **just-in-time** at the start of that session, not up front (later slices' plans depend on the code earlier slices land). `brainstorming` ran once to produce this spec and recurs only if a slice proves the spec wrong. A slice's **Definition of Done** (§7.2) is the signal to advance the `Next /goal:` cursor to the next slice. SLICE-0 is doc-only (no implementation plan).
#### SLICE-2 — Collection field schema + central validation → completes PUC-4
- **Depends on:** SLICE-1
- **DoD:** `.collection.yaml fields:` parsed (`enum`/`tags`/`text`); values validated on read (warn) and on write (reject); schema served via the collection API; no-`fields:` collections unchanged (INV-5).
- **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).
- **DoD:** list endpoint returns facet counts + honors filter params; left pane renders faceted groups with counts and tag-value search; filters compose (AND across fields).
- **DoD:** list endpoint returns facet counts + honors filter params (incl. `malformed`); left pane renders faceted groups with counts + tag-value search; filters compose.
- **DoD:** detail metadata panel renders schema controls; `POST …/meta` validates, direct-commits the sidecar, re-ingests; authorized by scope-role (INV-4); lazy-migrates a legacy entry on first edit.
- **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 action bar; `POST …/meta/bulk` applies set/add/remove as one commit; partial-rejection reported.
- **DoD:** multi-select + bulk bar; `POST …/meta/bulk` applies set/add/remove as one commit; partial-rejection reported.
### 12.3 Rollout / launch plan
### 7.3 Rollout / launch plan
Pre-v1, single production: ship slices in order to the RFC deployment; each minor-version bump carries §20 changelog + upgrade steps. The opt-in-per-collection nature (INV-5) means a deployment adopts it only when it declares a `fields:` block and (optionally) runs the migration.
Pre-v1, single production: ship slices in order; each minor bump carries §20 changelog + upgrade steps. Opt-inpercollection (INV-5): a deployment adopts it only by declaring a `fields:` block and (optionally) running the migration.
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Ben Stull