skills/25-HosungYou-Diverga/skills/orchestrator/SKILL.md
Unified Agent Teams orchestrator for Diverga v12.0.0. Manages Agent Teams creation, VS Arena debate, and subagent dispatch. Single entry point for all parallel/debate workflows. Replaces research-orchestrator and vs-arena skills. Triggers: orchestrator, agent team, create team, parallel agents, debate, competing, collaborate, VS Arena
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research orchestratorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Execution layer (HOW). Receives agent IDs, decides execution strategy, manages lifecycle.
Does NOT handle:
No circular dependency: coordinator calls orchestrator, never reverse. Orchestrator receives agent IDs and executes; it does not call back into the coordinator.
/diverga:orchestratorOrchestrator does NOT enforce research checkpoints. It trusts the caller (coordinator or user) to have resolved prerequisites.
.research/ context exists, read it; otherwise proceed without checkpoint gating.Request received
|
v
Check config.agent_teams.enabled
|
+-- false --> Always use subagents (Task with run_in_background)
|
+-- true --> Check CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS env var
|
+-- not set --> Subagent fallback + warn user
|
+-- set --> Evaluate scenario
|
+-- Inter-agent debate needed? --> Agent Teams
| (VS Arena, cross-method comparison, competing hypotheses)
|
+-- Parallel independent work? --> Agent Teams
| (multi-DB fetch, parallel review, concurrent analysis)
|
+-- Sequential pipeline? --> Subagents
| (G5->G6->F5 humanize, single agent tasks)
|
+-- Simple single agent? --> Direct Task dispatch
When config.agent_teams.enabled = true AND CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set.
Gather research context from diverga_project_status or user input:
research_question (from CP_RESEARCH_DIRECTION or user)paradigm (from CP_PARADIGM_SELECTION or user)research_field (e.g., Education, Psychology, HRD)target_journal (if available)key_variables (if available)Select 3 of 5 personas (V1-V5) based on paradigm:
| Rule | Always include 1 persona differing from CP_PARADIGM_SELECTION | |------|---------------------------------------------------------------|
| Paradigm | Selection | |----------|-----------| | Quantitative | V1 + V4 + one of V2/V3/V5 | | Qualitative | V4 + V1 + one of V2/V3/V5 | | Mixed | V3 + two of V1/V2/V4/V5 | | No paradigm set | V1 + V3 + V4 (maximum paradigmatic spread) |
All VS Arena personas run on opus.
Create the team and spawn 3 persona teammates:
TeamCreate("vs-arena-{topic}")
Spawn teammate for each selected persona with prompt:
- Research context (question, field, paradigm, variables, journal)
- Persona definition reference (agents/v{N}.md)
- Persona constraints reference (config/personas.json cannotRecommend)
- Instruction: provide exactly ONE methodology recommendation
Each persona investigates the research question independently. No inter-agent communication during this stage.
Teammates message each other directly via team mailbox (SendMessage):
Lead collects all positions and presents at CP_METHODOLOGY_APPROVAL:
## VS Arena: Methodology Recommendations
### Option A: [Persona] Recommendation
Methodology: [name]
T-Score: [score]
Rationale: [brief]
Cross-critique from other personas: [summaries]
### Option B: ...
### Option C: ...
Which methodology would you like to proceed with? (A/B/C)
WAIT for user selection. Record decision.
TeamDelete after user makes selection.
| Scenario | Team Name | Teammates | When |
|----------|-----------|-----------|------|
| VS Arena | vs-arena-{topic} | 3 of V1-V5 | CP_METHODOLOGY_APPROVAL or explicit request |
| Systematic Review | sr-pipeline-{topic} | I1 x3 (per DB) | I0 multi-DB fetch |
| Cross-Method | method-compare-{topic} | C1+C2+C3 | Competing design recommendations |
| Parallel Review | review-{topic} | 2-5 agents | Quality review from multiple angles |
| Custom | {user-specified} | User-specified | Explicit orchestrator call |
Users can request custom teams via natural language:
User: "/diverga:orchestrator create a team with C1 and C2 to compare
quantitative designs for my RCT study"
Orchestrator parses:
- agents: [C1, C2]
- purpose: competing design recommendations
- team_name: "design-compare-rct"
- teammate_count: 2
User: "Have 3 agents review my methodology section from different angles"
Orchestrator infers:
- agents: [X1 (ethics), B2 (quality), G2 (publication readiness)]
- purpose: parallel review
- team_name: "review-methodology"
- teammate_count: 3
Maximum teammates: 5 (per Claude Code best practices). If user requests more, suggest splitting into phases.
When teams are disabled or unavailable, all workflows fall back to subagent dispatch.
Same VS Arena stages, but:
Task(subagent_type="diverga:v{N}", model="opus", run_in_background=true) instead of team creationCross-critique is permanently unavailable in subagent mode. This is a known limitation, not a bug. The orchestrator compensates with its own synthesis.
All agents route to their designated model tier. Source of truth: config/agents.json.
| Category | Agent | Display Name | Tier | Model | |----------|-------|-------------|------|-------| | A: Foundation | A1 | Research Question Refiner | HIGH | opus | | | A2 | Theory & Critique Architect | HIGH | opus | | | A5 | Paradigm Advisor | HIGH | opus | | B: Evidence | B1 | Literature Scout | MEDIUM | sonnet | | | B2 | Quality Appraiser | MEDIUM | sonnet | | C: Design | C1 | Quantitative Design & Sampling | HIGH | opus | | | C2 | Qualitative Design (Ethnography/AR) | HIGH | opus | | | C3 | Mixed Methods Design | HIGH | opus | | | C5 | Meta-Analysis Master | HIGH | opus | | D: Collection | D2 | Data Collection Specialist | MEDIUM | sonnet | | | D4 | Instrument Developer | HIGH | opus | | E: Analysis | E1 | Quantitative Analysis & Code Gen | HIGH | opus | | | E2 | Qualitative Coding | HIGH | opus | | | E3 | Mixed Methods Integration | HIGH | opus | | F: Quality | F5 | Humanization Verifier | MEDIUM | sonnet | | G: Publication | G1 | Journal Matcher | MEDIUM | sonnet | | | G2 | Publication Specialist | MEDIUM | sonnet | | | G5 | Academic Style Auditor | MEDIUM | sonnet | | | G6 | Academic Style Humanizer | HIGH | opus | | I: Systematic Review | I0 | SR Pipeline Orchestrator | HIGH | opus | | | I1 | Paper Retrieval | MEDIUM | sonnet | | | I2 | Screening Assistant | MEDIUM | sonnet | | | I3 | RAG Builder | LOW | haiku | | X: Cross-Cutting | X1 | Research Guardian | HIGH | opus |
V1-V5 personas are not listed here -- they are always invoked through VS Arena at opus tier.
Always pass model parameter explicitly when dispatching:
# HIGH tier
Task(subagent_type="general-purpose", model="opus", ...)
# MEDIUM tier
Task(subagent_type="general-purpose", model="sonnet", ...)
# LOW tier
Task(subagent_type="general-purpose", model="haiku", ...)
Before creating a team, prompt the user:
"Agent Teams will spawn N independent sessions. Proceed?
[Y] Yes / [S] Subagents instead / [N] Cancel"
Skip this prompt if the user explicitly requested teams.
Autonomous modes (Sisyphus, OMC, ralph, ultrawork, ecomode) removed in v6.0. See CHANGELOG.md.
development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
testing
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
data-ai
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.