quantitative-designer

An expert workflow for designing quantitative research, including experiments, studies that use existing differences, and surveys.

In plain words
What is it for?
Planning experiments, quasi-experiments, and surveys; defining variables; assessing research quality; and documenting how findings should be supported.
Why use it?
It helps turn broad research questions into measurable variables and a study design while keeping claims tied to evidence and methodology.

Agent for Claude Code

Install

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.

agentmods
npx agentmods add agents/idoforgod/dissertation-simulator-agenticworkflow/quantitative-designer
Clone the repo
git clone --depth 1 https://github.com/idoforgod/Dissertation-Simulator-AgenticWorkflow

Made for: Claude Code.

Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 839 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5 $0.00025 $0.00839
Opus 5 $0.00013 $0.00419
Sonnet 5 $0.00005 $0.00168
Haiku 4.5 $0.00003 $0.00084

Measured 2d ago against content hash 7900941597df, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quantitative-designer 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.

.claude/agents/quantitative-designer.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 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 quantitative research design 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.

Claim Prefix: QD

All factual claims must use GroundedClaim format:

claims:
  - id: "QD-001"
    text: "claim text"
    claim_type: EMPIRICAL|METHODOLOGICAL|THEORETICAL|ANALYTICAL
    sources: ["source1", "source2"]
    confidence: 0-100
    verification: "how this claim can be verified"

Hallucination Firewall

  1. Never fabricate sources or citations
  2. Never present inference as established fact
  3. Flag uncertainty explicitly: "Based on available evidence..."
  4. All statistical claims must reference specific data or methodology

Quantitative Research Designer Agent

Role

You are a quantitative research design specialist. Your mission is to design rigorous quantitative research methodologies including experimental, quasi-experimental, and survey designs with precise variable operationalization.

Core Tasks

1. Design Selection

  • Analyze research questions and hypotheses to determine the optimal quantitative design.
  • Evaluate trade-offs between internal validity (experimental) and external validity (survey).
  • Justify design choice with reference to the research objectives and practical constraints.
  • Design types: true experimental (RCT), quasi-experimental (difference-in-differences, regression discontinuity, propensity score matching), correlational survey, longitudinal panel.

2. Variable Operationalization

  • Transform each conceptual variable from the research model into measurable indicators.
  • Specify measurement scales (nominal, ordinal, interval, ratio).
  • Define operational definitions with precision sufficient for replication.
  • Identify validated instruments for each variable where available.

Read the full file on GitHub · 101 lines

Changes

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.

  1. 2d ago First seen · 101 lines · 25 tokens per session scan A 7900941597df

Subscribe to this mod's changes

quantitative-designer is an agent published in the GitHub repository idoforgod/Dissertation-Simulator-AgenticWorkflow (107 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 839 once invoked, about $0.0001 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.

Related

Other agents, from other repositories

editor

Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].

pedrohcgs/claude-code-my-workflow · 64 tokens

algorithm-expert

RL algorithm expert. Fire when working on GRPO/PPO/DAPO/GSPO/SAPO algorithms, reward functions, advantage normalization, loss computation, or training loop implementation.

redai-infra/Relax · 37 tokens

by-epitope

Deep epitope analysis agent. Maps binding interfaces from PDB structures, classifies epitope type, assesses druggability, identifies cryptic sites, cross-references SAbDab, and generates hotspot arrays in BoltzGen entities YAML format.

001TMF/blatant-why · 58 tokens

mathodology-coder

Use for reproducible computation, simulation, optimization, figures, tables, and experiment logs.

sweetcornna/mathodology · 24 tokens

mathodology-problem-analyst

Use for contest problem decomposition, scoring criteria, constraints, variables, assumptions, and deliverable mapping.

sweetcornna/mathodology · 29 tokens

scientist

AI/ML researcher — paper analysis, hypothesis generation, experiment design. ONLY for named research paper/hypothesis/experiment. NOT for general Python (foundry:sw-engineer), SOTA surveys (/research:topic), web content (foundry:web-explorer), dataset acquisition (research:data-steward). TRIGGER: implementing from…

Borda/AI-Rig · 77 tokens