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Sprint 3 closure for v2.8.0. Brings the 2 new top-level domains (business-operations + commercial) to release-ready by extending the cross-platform sync infrastructure, the docs generator, and the MkDocs nav to recognize them. ## Cross-platform sync (codex / gemini / hermes) - scripts/sync-codex-skills.py — SKILL_DOMAINS extended with business-operations + commercial. Regenerated .codex/skills/ symlinks for 15 new skills + .codex/skills-index.json with full descriptions. - scripts/sync-gemini-skills.py — DOMAIN_MAP extended with all 5 v2.7.0+ v2.8.0 top-level domains (productivity, marketing-top-level, research, business-operations, commercial). +30 items synced. - scripts/sync-hermes-skills.py — DOMAIN_DIRS extended with business-operations + commercial. ## Docs generation (Pass 2 command/agent discovery) scripts/generate-docs.py extended with: - DOMAINS dict extended with business-operations (sort=13) and commercial (sort=14) entries. - Pass 2 for agent discovery — walks <domain>/agents/<agent>.md (v2.8.0 pattern), in addition to <domain>/<plugin>/agents/<agent>.md (legacy pattern). - Pass 2 for command discovery — walks <domain>/commands/<cmd>.md (v2.8.0 pattern) AND <domain>/<skill>/commands/<cmd>.md (v2.7.0 pattern). Previously, only root-level commands/*.md were discovered; 35 commands were orphaned (v2.7.0 capture/pulse/landing/etc. + all v2.8.0 commands). Result: 311 skill pages + 75 agent pages + 69 command pages = 455 total. Up from 311 + 73 + 34 = 418. ## MkDocs nav mkdocs.yml updated with: - Business Operations section (7 sub-skill nav entries) - Commercial section (8 sub-skill nav entries) - 2 new orchestrator agents added to Agents nav - 17 new v2.8.0 slash commands added to Commands nav MkDocs build succeeds (non-strict) in ~17s. Strict mode flags 3 pre- existing broken links in older content (cs-aeo, grill-with-docs) — out of scope for v2.8.0. ## CHANGELOG.md v2.8.0 entry rewritten from "Sprint 1 only" to the full Sprint 1 + 2 + 3 view. All 13 sub-skills documented with canon attribution. Stats updated: - 313 -> 328 skills (+15) - 12 -> 14 top-level domains - 60 -> 77 slash commands (+17) - 402 -> 441 Python tools (+39) - 542 -> 581 reference docs (+39) - 46 -> 48 cs-* agents (+2) - 57 -> 59 marketplace plugins (+2) - 34 -> 69 documented commands in MkDocs (+35) ## Root CLAUDE.md Updated Current Scope + Current Version to reflect v2.8.0 (released) status. Sprint 1 "in-flight" -> "complete". Counts updated to 328 skills / 441 tools / 77 commands. ## Per-skill audit (scripts/audit_skills.py) Ran across 329 total skills. All 13 v2.8.0 sub-skills audited with skill_review_checklist_runner.py: 1 score 5/6, 7 score 4/6, 4 score 3/6, 1 score 2/6 (knowledge-ops). Dominant failure mode: rule #2 "SKILL.md under 100 lines" — known tension with our deliberate Forcing-question library depth (mandatory per user direction). Tracked as ADVISORY for skills that deliberately expose extended grill discipline. ## Plugin manifest validation scripts/check_plugin_json.py --all passes (exit 0) for all 47 plugin manifests including the 2 new ones. The PR #690 validator recognizes the source extension field per CLAUDE.md. https://claude.ai/code/session_015bBb4HzWCf5HH5QK2TGtnW
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| title | description |
|---|---|
| /cs-process-map — Slash Command for AI Coding Agents | Map an internal business process (BPMN-style swim lanes), measure cycle time, and detect bottlenecks where work spends most of its time waiting. Slash command for Claude Code, Codex CLI, Gemini CLI. |
/cs-process-map
:material-console: Slash Command
:material-github: Source
Run the process-mapper skill on this input:
$ARGUMENTS
Three-tool workflow
-
process_documenter.py— Document the process as a BPMN-ish ASCII swim lane diagram. Input: stage list (name, owner, type{value-add/wait/rework}, P50 + P90 duration). Output: markdown diagram + normalized JSON. -
bottleneck_detector.py— Identify bottlenecks. Triggers: stage P50 > 2× mean of value-add stages, OR wait-state % > 40% of total, OR rework % > 15%. Tunable via--profile {saas,services,manufacturing,healthcare}. -
cycle_time_analyzer.py— Compute total cycle time (P50, P90), value-add ratio (VA%), Little's Law throughput. Verdict: VA% > 25% HEALTHY / 10-25% TYPICAL / <10% WASTE-HEAVY.
Output
- Process diagram (markdown)
- Bottleneck list with severity + recommended action
- Cycle-time scorecard with VA% verdict
- Top 3 next actions
Distinct from
engineering/slo-architect— that's system reliability with SLO/SLI. This is business process reliability.engineering/llm-wiki— that's personal PKM. This is company process documentation.c-level-advisor/coo-advisor— that's strategic COO judgment. This is tactical process mapping.