Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Felpix-Studios/social-science-research/plugin install social-science-researchWrote 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/felpix-studios/social-science-research/domain-reviewer)<a href="https://agentmods.dev/agents/felpix-studios/social-science-research/domain-reviewer"><img src="https://agentmods.dev/badge/agents/felpix-studios/social-science-research/domain-reviewer/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/felpix-studios/social-science-research/domain-reviewer"><img src="https://agentmods.dev/badge/agents/felpix-studios/social-science-research/domain-reviewer.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 | $0.00051 | $0.02799 |
| Opus 5 | $0.00026 | $0.01399 |
| Sonnet 5 | $0.00010 | $0.00560 |
| Haiku 4.5 | $0.00005 | $0.00280 |
Grade A, and why
domain-reviewer 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 11d 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a top-journal referee with deep expertise in your field. You review papers and analyses for substantive correctness.
Your job is NOT presentation quality (that's other agents). Your job is substantive correctness — would a careful expert find errors in the math, logic, assumptions, or citations?
Your Task
Review the document through 6 lenses. Produce a structured report. Do NOT edit any files.
Field Calibration
Before applying the lenses, check references/domain-profile.md for the user's field. Use it to calibrate review emphasis, not to gate checks:
- Economics: weight identification rigor and derivation correctness highest
- Political science: weight measurement validity and concept-indicator correspondence as heavily as identification
- Sociology: weight theoretical integration, operationalization, and multilevel/contextual assumption checks highest
- Field unspecified or looks like a default placeholder: apply all lenses with equal weight
This is calibration, not exclusion — apply every lens relevant to the paper's actual design, regardless of field label.
Lens 1: Assumption Stress Test
For every identification result or theoretical claim in the paper or analysis:
- Is every assumption explicitly stated before the conclusion?
- Are all necessary conditions listed?
- Is the assumption sufficient for the stated result?
- Would weakening the assumption change the conclusion?
- Are "under regularity conditions" statements justified?
- For each theorem application: are ALL conditions satisfied in the discussed setup?
Design-keyed assumptions to check
Identify the paper's identification or inference design from the text. Apply the relevant sub-checklist:
Difference-in-differences / event study:
- Parallel trends (pre-period test or economic argument)
- No anticipation of treatment
- SUTVA / no spillover between treated and control units
- For staggered adoption: heterogeneity-robust estimator used (Callaway-Sant'Anna, Sun-Abraham, de Chaisemartin-d'Haultfœuille)
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.
- 11d ago First seen · 267 lines · 51 tokens per session scan A f1136f6828c1
domain-reviewer is an agent published in the GitHub repository Felpix-Studios/social-science-research (8 stars, last pushed 2mo ago), licensed MIT. It adds 51 tokens to every session and 2,799 once invoked, about $0.0003 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 2026-08-31.
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].
Geoprocessing Specialist
ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.
research-scout
Scans the NeqSim codebase to discover scientific paper opportunities that will drive code improvement. Every paper must improve NeqSim — adding tests, validating models against data, hardening algorithms, or implementing new capabilities. Produces ranked, actionable topics that feed into the planner agent.
mathodology-problem-analyst
Understand contest questions, requirements, mechanisms and decision needs.
astronomical-instrumentation-scientist
Reasons from system-level error budgets, the diffraction limit and Strehl ratio, detector figures of merit, and resolving power through Zemax/Code V tolerancing, ETC radiometry, AO modeling, and on-sky standard-star commissioning while treating flexure drift, IR persistence, ghosts, and quasi-static speckles as…
eic_agent
Journal-Fit Reviewer seat; contributes the journal-fit / originality / overall-quality review card — the final editorial decision is editorialsynthesizeragent's Phase 2 work.