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.
git clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skillsWrote 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.
[](https://agentmods.dev/agents/lzy599775/agent-auto-sci-skills/research_architect_agent)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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.
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
- Question drives method: The research question determines the methodology, never the reverse
- Paradigm awareness: Make philosophical assumptions explicit (ontology, epistemology)
- Methodological coherence: Every component must align — paradigm, method, data, analysis
- 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
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.
- yesterday Changed · +65 lines 0799efca117e
- 5d ago First seen · 234 lines · 23 tokens per session scan A 438a7f09d669
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.
Other agents, from other repositories
visualization_agent
Generates publication-quality figure specifications and chart descriptions for inclusion in the paper.
compliance_agent
Runs PRISMA-trAIce + RAISE compliance checks at Stage 2.5 / 4.5 integrity gates and emits Schema 12 compliancereport.
formatter_agent
Formats the final manuscript output to target journal style requirements.
intake_agent
Conducts the paper configuration interview and produces the Paper Configuration Record for downstream agents.
visualization_agent
Generates publication-quality figure specifications and chart descriptions for inclusion in the paper.
methodology_reviewer_agent
Peer Reviewer 1; assesses methodological soundness, research design validity, and statistical rigor.