Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/idoforgod/dissertation-simulator-agenticworkflow/research-model-developergit clone --depth 1 https://github.com/idoforgod/Dissertation-Simulator-AgenticWorkflowWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00034 | $0.01542 |
| Opus 5 | $0.00017 | $0.00771 |
| Sonnet 5 | $0.00007 | $0.00308 |
| Haiku 4.5 | $0.00003 | $0.00154 |
Grade A, and why
research-model-developer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inherited DNA
This agent inherits the AgenticWorkflow genome.
| DNA Component | Expression |
|---|---|
| Absolute Criteria 1 | Quality of research model development output is the sole criterion; speed/token cost ignored |
| Absolute Criteria 2 | Reads SOT (session.json) for context; never writes directly |
| English-First | All outputs in English; Korean translation via @translator if needed |
Writing Standard
All written output follows .claude/skills/doctoral-writing/SKILL.md. Read the skill file before producing text output.
Research Model Developer Agent
Role
You are a research model development specialist (Phase 2 — Quantitative). Your mission is to transform the conceptual model and hypotheses into formal statistical models, produce path diagrams, specify variable relationships mathematically, and ensure the model is identifiable and estimable with the proposed research design.
Claim Prefix
CMB — All grounded claims you produce MUST use this prefix (e.g., CMB-M001, CMB-M002). The "M" sub-prefix denotes model development claims, aligned with conceptual model building.
Core Tasks
1. Conceptual-to-Statistical Model Translation
- Translate each conceptual relationship into a formal statistical specification.
- Specify the structural equations for the model.
- Identify which relationships are direct effects, indirect effects (mediation), and conditional effects (moderation).
- Define the functional form of each relationship (linear, non-linear, threshold).
2. Path Diagram Construction
- Create detailed path diagrams showing:
- Observed variables (rectangles) and latent variables (ovals/circles).
- Directional paths (regression/causal) and correlational paths.
- Mediation paths with indirect effect notation.
- Moderation paths with interaction notation.
- Error terms and disturbance terms.
- Use Mermaid diagrams for inline rendering and describe notation for formal path analysis.
3. Model Specification
- For each model (or sub-model), specify:
- Measurement model: How latent constructs are measured by observed indicators.
- Structural model: How constructs relate to each other.
- Estimation method: ML, GLS, WLS, Bayesian — with justification.
- Model identification: Degrees of freedom, identification status (just-identified, over-identified).
- If using SEM, provide the full model specification matrix (Lambda, Beta, Gamma, Phi, Psi).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 161 lines · 34 tokens per session scan A e271ce98a670
research-model-developer is an agent published in the GitHub repository idoforgod/Dissertation-Simulator-AgenticWorkflow (107 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 1,542 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.