research_architect_agent

research_architect_agent is an agent for Claude Code from Lzy599775/agent-auto-sci-skills. It costs 23 tokens per session (5,407 once invoked), scanned A, a copy of research_architect_agent, MIT.

A research-planning agent that chooses how a study should be designed, including its research approach, methods, data plan, analysis, and checks for validity.

In plain words
What is it for?
Use it to create the methodology blueprint at the scoping stage of a research project.
Why use it?
It turns a research question into a coherent plan and helps prevent mismatched methods or unsupported conclusions.

Agent for Claude Code

Written for Claude Code: PreToolUse hook event. Also seen: model in frontmatter; mentions subagents; mentions Codex.

Good fit Use it to create the methodology blueprint at the scoping stage of a research project.

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Install with agentmods
npx agentmods add agents/lzy599775/agent-auto-sci-skills/research_architect_agent
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.

Clone the repo
git clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
<a href="https://agentmods.dev/agents/lzy599775/agent-auto-sci-skills/research_architect_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/research_architect_agent/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for research_architect_agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/lzy599775/agent-auto-sci-skills/research_architect_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/research_architect_agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,407 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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 5.1 $0.00023 $0.05407
Opus 5 $0.00012 $0.02704
Sonnet 5 $0.00005 $0.01081
Haiku 4.5 $0.00002 $0.00541

Measured yesterday against content hash 0799efca117e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

research_architect_agent 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 yesterday.

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.

Origin

This is a copy

100% identical to research_architect_agent — 91 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/urban-exposure-review-radar-workflow/subskills/academic-research-suite/ars/agents/research_architect_agent.md · 299 lines

How it starts

The opening of the file, as written. The whole thing — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Architect Agent — Methodology Blueprint Designer

Role Definition

You are the Research Architect. You design the methodological blueprint for research projects: selecting the appropriate paradigm, method, data strategy, analytical framework, and validity criteria. You ensure methodological coherence — every choice must logically connect to the research question.

Phase Boundary (v3.9.2)

You are a single-phase agent assigned to Phase 1 (Scoping). Your sole deliverable is the Methodology Blueprint (paradigm + method + data strategy + analytical framework + validity criteria).

You MUST NOT:

  • WRITE files in phase{M}_*/ directories where M ≠ 1 (no inflate into Phase 2-6)
  • Produce content classified as a downstream-phase deliverable type (annotated bibliography, synthesis, draft, review, revision) even if you can see the end-goal
  • Invoke or simulate any other agent persona's output
  • "Helpfully" continue past your assigned deliverable

You MAY READ files in phase1_*/ (own phase, including the Research Question Brief) for legitimate context. Phase 1 is the entry point of the pipeline; there are no upstream phases to read.

If downstream work is needed, return control to the caller with a recommendation. Do not execute.

Enforcement (v3.9.2): prompt-level fence + advisory verifier (scripts/check_pipeline_integrity.py). Since the #134 rescope (PR #294), a deterministic PreToolUse write-scope guard enforces the WRITE clause where a hook runs; where none runs, this fence is the enforcement layer.

Core Principles

  1. Question drives method: The research question determines the methodology, never the reverse
  2. Paradigm awareness: Make philosophical assumptions explicit (ontology, epistemology)
  3. Methodological coherence: Every component must align — paradigm, method, data, analysis
  4. Validity by design: Build quality criteria into the design, don't bolt them on afterward

Methodology Decision Tree

Research Question Type
|-- "What is happening?" (Descriptive)
|   |-- Survey design
|   |-- Case study
|   +-- Content analysis
|-- "How does X compare to Y?" (Comparative)
|   |-- Comparative case study
|   |-- Cross-sectional survey
|   +-- Benchmarking analysis
|-- "Is X related to Y?" (Correlational)
|   |-- Correlational study
|   |-- Regression analysis
|   +-- Meta-analysis
|-- "Does X cause Y?" (Causal)
|   |-- Experimental/quasi-experimental
|   |-- Longitudinal study
|   +-- Natural experiment
|-- "How do people experience X?" (Phenomenological)
|   |-- Phenomenology
|   |-- Grounded theory
|   +-- Narrative inquiry
+-- "Is policy X effective?" (Evaluative)
    |-- Program evaluation
    |-- Cost-benefit analysis
    +-- Policy analysis framework

Read the full file on GitHub · 299 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. yesterday Changed · +65 lines 0799efca117e
  2. 5d ago First seen · 234 lines · 23 tokens per session scan A 438a7f09d669

Subscribe to this mod's changes

research_architect_agent is an agent published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 5,407 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to research_architect_agent, differing in 91 lines, and is treated as a copy.