Three independent improvements bundled because they share the same
surface (workflow/agent customization) and landed from the same design
discussion:
## Fallback sentence disambiguated (7 SKILL.md files)
The "if the script fails" fallback used to say `{project-root}/_bmad/
custom/{skill-name}.toml` for the team override and then just `{skill-
name}.user.toml` for the user override, leaving the user file's
location implicit. LLMs could reasonably guess skill root or project
root instead. Replaced with an unambiguous numbered list that spells
out the full path for every file in the merge chain.
## Product-brief: stage promotion + brief_template variable
- Promoted `## Stage 1: Understand Intent` from a nested step inside
"On Activation" to a top-level section. The previous "Step 7: Stage
1 — Understand Intent → Proceed to Stage 1 below" was mechanical
numbering pretending to be a step. Activation now ends cleanly at
Step 6; Stage 1 is a peer section.
- Added `brief_template` as a workflow-level scalar customization
defaulting to `resources/brief-template.md`. Stage 4 reads
`{workflow.brief_template}` instead of the hardcoded path, so orgs
can point at their own template under `{project-root}/...` without
forking the skill.
## New doc: docs/how-to/extend-bmad-for-your-org.md
Four worked recipes that together cover most enterprise scenarios:
1. Shape an agent across every workflow it dispatches (dev agent +
Context7 MCP + Linear search — the highest-leverage pattern)
2. Enforce org conventions inside a specific workflow (product-brief
+ compliance-field persistent_facts)
3. Publish completed outputs to external systems (product-brief +
Confluence + Jira via MCP, gated on user confirmation for Jira)
4. Swap in your own output template (product-brief + brief_template
variable swap)
Opens with the two-layer mental model (agent spans workflows,
workflow is local) so readers pick the right granularity before
reading any recipe. Closes with a "Combining Recipes" section
showing all four composed. Cross-linked from customize-bmad.md.
## Validation
- Resolver: workflow.brief_template returns the default cleanly.
- validate-file-refs.js: 254 files scanned, 146 refs checked
(+7 from this commit), 0 broken.
Completes the customization surface rollout by giving the product-brief
workflow the same override model as the six BMad agents, under the
[workflow] namespace instead of [agent].
## customize.toml
Mirrors the agent shape under [workflow] with:
- activation_steps_prepend / activation_steps_append (harmonized across
agents and workflows — same field names, same append semantics)
- persistent_facts with the file: convention, seeded with
file:{project-root}/**/project-context.md
- on_complete scalar (renamed from PR #2282's skill_end for clarity —
reads cleaner as "what runs when the workflow completes")
## SKILL.md
7-step workflow activation:
1. Resolve workflow block
2. Execute prepend steps
3. Load persistent facts (file: or literal)
4. Load config
5. Greet if not already
6. Execute append steps
7. Stage 1 — Understand Intent
python3 + stdlib tomllib invocation; no uv required.
## Prompt file changes
- Path normalization: ../agents/ → agents/, ../resources/ → resources/,
bare foo.md → prompts/foo.md. All references now resolve from the
skill root (matches the convention documented in SKILL.md).
- Paths: meta-line added to each of the 4 prompt files that reference
other files, reinforcing "bare paths resolve from skill root" so the
LLM doesn't lose the convention when operating two hops into a
prompt chain.
- finalize.md terminal stage now calls the resolver for
workflow.on_complete — non-empty values run as the final step.
## Validation
- Resolver output verified: 4 workflow fields returned cleanly.
- validate-file-refs.js: 254 files scanned, 139 refs checked, 0 broken.
- test:refs: passing.
Three-layer customization (skill defaults → team → user) for BMad agents
and any skill that opts in. Users edit `_bmad/custom/{skill-name}.yaml`
(team, committed) or `{skill-name}.user.yaml` (personal, gitignored);
customizations survive updates.
Resolver is a Python script using PEP 723 inline metadata, invoked via
`uv run` so deps auto-install into a cached isolated env on first call.
This aligns with Anthropic's Agent Skills spec and BMB conventions, and
keeps the dependency declared (scannable by pip-audit/Dependabot) rather
than vendored.
## Design choices
- **Agent identity is hardcoded** in SKILL.md (name, title, Overview prose)
so skills can be invoked reliably by role *or* default name. Brand
recognition is preserved; customization shapes behavior, not identity.
- **Luminary-anchored personas** (e.g. "Channels Martin Fowler's
pragmatism and Werner Vogels's cloud-scale realism") deliver ~55%
token savings per agent while preserving distinctive voice beats.
- **Universal per-field merge rules** with v6.1-compatible agent
semantics: metadata shallow-merge, persona replace, critical_actions
and memories append, menu merge-by-code, all else deep-merge.
- **Workflow customization** shares the same surface — `bmad-product-brief`
pilots `activation_steps_prepend`, `activation_steps_append`, and
`skill_end` hooks that any workflow-style skill can adopt.
## Infrastructure
- `_bmad/scripts/` houses shared Python scripts (resolver + future).
- `_bmad/custom/` is provisioned empty with a seeded `.gitignore` for
`*.user.yaml` on fresh installs.
- Installer filters ensure `scripts/`, `custom/`, and sidecar-generated
`memory/` directories are never treated as modules.
- Dead v6.1 code cleaned up: `_config/agents/` no longer created,
`metadata.capabilities` removed from schema and CSV manifest.
Replace bmad-create-product-brief (step-based wizard) and
bmad-product-brief-preview (multi-agent) with a single unified
bmad-product-brief skill. Remove accidentally duplicated market
research step files and template. Update research skill
descriptions to use more natural trigger language.
Brian Madison