feat(skills): add research skill for web-sourced reference file generation

Standalone /research skill that scans the codebase, discovers canonical
sources via websearch, reads and deepens in parallel via subagents, and
writes structured topic files + sources.md to an explicit output path.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.agents/skills/research/references/file-format.md

@@ -0,0 +1,39 @@
+# Reference file format
+
+Every topic file follows this structure.
+
+## Frontmatter
+
+```yaml
+---
+topic: <topic-slug>          # matches the filename without .md (e.g. "api-reference")
+source_keys:                 # kebab-case slugs of sources that contributed; must match sources.md entries
+  - <slug>
+  - <slug>
+---
+```
+
+## Body
+
+Plain prose organized into markdown sections (`##`, `###`). Extract the content most relevant to skill authoring or implementation — not a verbatim copy of the source. Focus on:
+- Decisions that affect how to call the API or tool
+- Options, flags, or parameters with non-obvious behavior
+- Constraints, rate limits, or gotchas
+- Canonical patterns the skill should follow
+
+No inline URLs in the body — all source traceability lives in `sources.md` via `source_keys`.
+
+## sources.md format
+
+```markdown
+# Sources
+
+## <slug>
+
+- **URL:** <full URL>
+- **Description:** <one-line summary of what this source covers>
+- **Contributing files:** <comma-separated list of topic files this source contributed to>
+- **Status:** `extracted` | `no content extracted`
+```
+
+Use one `##` section per source. Slugs are kebab-case derived from the domain or page title (e.g. `stripe-api-docs`, `openai-python-sdk-readme`).