Agent skill

Popdevr Research Design

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables…

MITAuto-check passedResearch & Science

Install Popdevr Research Design

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-research-design -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-research-design --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-research-design .claude/skills/popdevr-research-design && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
popdevr-research-design
GitHub stars
1.2k
Token cost
~2k tokens
SKILL.md length
823 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables…

  • Works in 3 steps: Definitions and coverage. Are the… → Data class and vintage. Mixing a… → Like-with-like comparison. Where full…
  • Defending the research design of a Population and Development Review (PDR
  • SKILL.md covers When to trigger, Match the method to the question, When the question is causal… and The adjudication test…, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Popdevr Research Design is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables, decomposition, event-history, age-period-cohort, projections) and, where the question is causal, defending identification, with the population-and-development linkage made explicit. PDR judges each method on its own terms and asks what it shows about development. Strengthens the design; it does not write code.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Defending the research design of a Population and Development Review (PDR
  • Wiley / Population Council) manuscript — choosing among demographic methods (life tables
  • Age-period-cohort
  • Projections) and

Example prompts

  • “/popdevr-research-design”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Definitions and coverage. Are the demographic concepts (a "birth," a "migrant," an age cutoff) and
  2. Data class and vintage. Mixing a high-quality register with a single DHS round, or different WPP
  3. Like-with-like comparison. Where full comparability is impossible, restrict to the subset that is

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Popdevr Research Design loads about 2k tokens when it runs. Until then it costs about 127 tokens; SKILL.md has 823 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~127
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 823 words, ~1,967 tokens.

Download SKILL.mdSave it as .claude/skills/popdevr-research-design/SKILL.md (or your agent's skills folder).
name
popdevr-research-design
description
Use when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables, decomposition, event-history, age-period-cohort, projections) and, where the question is causal, defending identification, with the population-and-development linkage made explicit. PDR judges each method on its own terms and asks what it shows about development. Strengthens the design; it does not write code.

Research Design (popdevr-research-design)

PDR accepts a wide range of approaches — empirical demography, formal demography, and conceptual synthesis — but is demanding about each, and it asks one extra question: does the design illuminate the population-and-development linkage, not just a demographic quantity? The design must credibly connect the argument (popdevr-theory-building) to evidence a broad readership will trust. This skill is method-aware: pick the section that matches your question and defend it against the strongest rival.

When to trigger

  • Choosing the method that actually answers a population-and-development question
  • A reviewer questioned the rate construction, the identification, or the development linkage
  • Specifying a decomposition, event-history, age-period-cohort, or projection design
  • Justifying why your design adjudicates the rival account from popdevr-literature-positioning

Match the method to the question

  • Life tables — for survival, life expectancy, and exposure: period vs. cohort, abridged vs. complete; multiple-decrement (cause-specific) where the development story is cause-specific.
  • Decomposition — to attribute a difference or change in a rate to components: Kitagawa (rate vs. composition), Arriaga (age contributions to e0), Das Gupta (multi-factor). Say exactly what each component means and which maps to a development channel.
  • Event-history / survival — for timing and transitions (first birth, migration, mortality), with competing risks where several destinations matter; check the proportional-hazards assumption.
  • Age-period-cohort — confront the identification problem head-on: state the constraint or modeling assumption (and its justification); do not present a single "identified" APC partition as assumption-free.
  • Projections / cohort-component — make transition rates, the base population, and assumptions (closed/open, period/cohort, policy scenarios) explicit; report sensitivity to key assumptions; PDR values scenario projections tied to development or policy futures.

When the question is causal (population ↔ development)

  • Identification first. State the estimand and the assumptions licensing a causal reading (ignorability, parallel trends, exclusion, continuity); defend them, do not assert them.
  • Selection and exposure are demographic hazards: mortality selection, migration selection, and differential exposure can masquerade as effects — address them explicitly.
  • Two-way causation. Population and development often co-move; name the direction you claim and the observable that separates it from the reverse (reverse causation, institutional confounding).
  • Inference. Cluster at the right level (household, region, country); use survey/design weights; report uncertainty for derived quantities.
  • Sensitivity. How strong must an unobserved confounder (or a violated assumption) be to overturn it?

The adjudication test (PDR-specific)

For the single strongest rival explanation (e.g., reverse causation, compositional change, selection, institutional confounding), write one sentence: "If the rival were true rather than my account, the pattern would look like ___; instead it looks like ___." If you cannot, the design does not yet identify the population-and-development contribution.

Show full SKILL.md (409 more words)Show less

Cross-country comparability (a recurring PDR design problem)

PDR papers often compare countries or development contexts, and a cross-national contrast is only as good as its comparability. Before reading a between-country gap as a development effect, settle three things:

  1. Definitions and coverage. Are the demographic concepts (a "birth," a "migrant," an age cutoff) and the denominators measured the same way across settings? Vital-registration coverage and census quality vary with development level — and that variation can create the gradient you are studying.
  2. Data class and vintage. Mixing a high-quality register with a single DHS round, or different WPP vintages, can manufacture artefactual differences. Hold the data class and vintage as constant as the question allows, and report what you could not harmonize.
  3. Like-with-like comparison. Where full comparability is impossible, restrict to the subset that is comparable, or model the measurement difference explicitly rather than absorbing it into the estimate.

State which of these you have controlled and which remain a caveat in popdevr-tables-figures notes.

When the contribution is a synthetic essay (no new estimate)

If the paper's contribution is a framework rather than an analysis, the "design" is the argument architecture: the propositions, the evidence marshaled for each, and the boundary where the framework stops applying. Route the rigor through popdevr-theory-building and popdevr-writing-style instead of this skill's estimation machinery, but still pass the adjudication test against the prior framework it revises.

Execution bridge (StatsPAI / Stata MCP)

Estimate and audit the design, don't only describe it. Full map: execution-with-mcp. PDR is population studies blending quantitative and policy work; apply the chain to its empirical-causal papers.

  • detect_design → recommend → fit with as_handle=true → audit_result.
  • Observational causal claims: staggered DiD (callaway_santanna / sun_abraham + bacon_decomposition + honest_did_from_result); IV (effective_f_test + anderson_rubin_ci); RDD (rdrobust + mccrary_test).
  • Experiments: randomization-based inference, romano_wolf for many-outcome family-wise control, and mediate for mediation (not naive controlling-away).
  • Sensitivity: oster_delta / sensemakr for observational claims.

Report the effect size in interpretable units; route the full battery to the appendix/supplement. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.

Anti-patterns

  • Running a regression when the question calls for a life table, a decomposition, or an event-history model
  • Presenting an APC decomposition without naming the identifying constraint
  • Period rates read as cohort experience (or vice versa) without justification
  • Ignoring mortality/migration selection or the population↔development direction of causation
  • Projections whose assumptions are buried instead of varied and reported

Output format

【Method】life table / decomposition / event history / APC / projection / causal
【Quantity / estimand】what is measured or identified + its development linkage
【Key assumption(s)】and how each is defended (name the APC constraint if used)
【Rival ruled out】the adjudication sentence (incl. reverse causation if relevant)
【Robustness/sensitivity】planned checks
【Next】popdevr-data-analysis

Supplementary resources

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Population-and-Development-Review-Skills/skills/popdevr-research-design of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

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GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
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Last30daysmvanhorn/last30days-skill64k—~7.9kAutomated safety check: NotesMIT

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Questions about Popdevr Research Design

What does Popdevr Research Design do?

A skill your agent uses when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables…. Popdevr Research Design is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables, decomposition, event-history, age-period-cohort, projections) and, where the question is causal, defending identification, with the population-and-development linkage made explicit.

When should I use Popdevr Research Design?

Popdevr Research Design fits situations like: defending the research design of a Population and Development Review (PDR; wiley / Population Council) manuscript — choosing among demographic methods (life tables; age-period-cohort; projections) and.

How do I install Popdevr Research Design in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-research-design -a claude-code`. Or copy the skill folder (Population-and-Development-Review-Skills/skills/popdevr-research-design in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/popdevr-research-design in your project. Claude Code loads it when a task matches its description.

How do I install Popdevr Research Design in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-research-design -a codex`. Or copy the skill folder (Population-and-Development-Review-Skills/skills/popdevr-research-design in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/popdevr-research-design in your project. Codex loads it when a task matches its description.

Can I use Popdevr Research Design in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-research-design -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/popdevr-research-design, .gemini/skills/popdevr-research-design, .github/skills/popdevr-research-design and .opencode/skills/popdevr-research-design in your project.

What does Popdevr Research Design need to run?

SKILL.md names no scripts, command-line tools or credentials: Popdevr Research Design is instructions for the agent only.

Does Popdevr Research Design access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Popdevr Research Design safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Popdevr Research Design use?

Popdevr Research Design is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Popdevr Research Design use?

About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Popdevr Research Design?

Skills that share tags, products or a category with Popdevr Research Design: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Popdevr Research Design?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.