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Agent skill

Psychrev Boundary Conditions

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

A skill your agent uses when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable.

MITAuto-check passed

Install Psychrev Boundary Conditions

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill psychrev-boundary-conditions -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills psychrev-boundary-conditions --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/Psychological-Review-Skills/skills/psychrev-boundary-conditions .claude/skills/psychrev-boundary-conditions && 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
psychrev-boundary-conditions
GitHub stars
1.2k
Token cost
~1.1k tokens
SKILL.md length
502 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable.

  • Works in 3 steps: Scope (the explanatory boundary) → Identifiability (for… → What it does NOT explain
  • Setting the scope of a Psychological Review theory — what it explains
  • SKILL.md covers When to trigger, Why scope is a contribution,…, Checklist and Anti-patterns, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Psychrev Boundary Conditions is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable. Bounds the theory; it does NOT derive its predictions (psychrev-argument-development) or frame its advance over rivals (psychrev-contribution-framing).

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

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

  • Setting the scope of a Psychological Review theory — what it explains
  • What it does NOT
  • (for formal models) whether its parameters are identifiable

Example prompts

  • “/psychrev-boundary-conditions”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Scope (the explanatory boundary)
  2. Identifiability (for formal/computational models)
  3. What it does NOT explain

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

Psychrev Boundary Conditions loads about 1.1k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 502 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~86
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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). 502 words, ~1,112 tokens.

Download SKILL.mdSave it as .claude/skills/psychrev-boundary-conditions/SKILL.md (or your agent's skills folder).
name
psychrev-boundary-conditions
description
Use when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable. Bounds the theory; it does NOT derive its predictions (psychrev-argument-development) or frame its advance over rivals (psychrev-contribution-framing).

Boundary Conditions, Scope & Identifiability (psychrev-boundary-conditions)

When to trigger

  • Your theory reads as if it explains everything (a red flag to reviewers)
  • You have not said where the theory stops holding
  • For a formal model: you have not checked whether distinct parameter settings are distinguishable
  • A reviewer will ask "what would falsify this?" or "can you even estimate that parameter?"

Why scope is a contribution, not a confession

At Psychological Review, stating where a theory holds and where it fails is part of the theory itself, not a limitations paragraph tacked on at the end. A theory that "explains everything" explains nothing — unbounded scope signals an unfalsifiable model. Editors read explicit boundaries as a sign of theoretical maturity. Three kinds of limit must be stated.

1. Scope (the explanatory boundary)
  • Phenomena in scope vs. phenomena explicitly out of scope (left to other processes).
  • Population / domain limits — does the theory claim to hold across development, species, cultures, tasks, or only within a stated range?
  • Level of analysis — computational, algorithmic, or implementational (Marr); be consistent, and theorize level shifts rather than sliding between them.
  • Conditions of breakdown — name the regime where the mechanism should stop producing the phenomena, and treat that prediction as a test of the theory.
2. Identifiability (for formal/computational models)

This is the modeling-specific boundary reviewers probe hardest:

  • Structural identifiability — can the parameters, in principle, be recovered from the kind of data the theory addresses, or do different settings produce identical predictions (a mimicry problem)?
  • Parameter recovery — demonstrate, by simulation, that fitting the model to data it generated recovers the true parameters; report where recovery degrades.
  • Model mimicry — can your model and a rival mimic each other on the available data? If so, the comparison is not diagnostic; say what data would separate them.
  • Sloppiness / sensitivity — note parameters the predictions barely depend on (and resist over-interpreting them).
Show full SKILL.md (195 more words)Show less
3. What it does NOT explain

A short, explicit list of phenomena the theory deliberately does not address, with one line each on why (out of scope vs. genuinely open). This pre-empts the "but it can't handle Y" reviewer objection by conceding Y on your own terms.

Checklist

  • Phenomena in scope and explicitly out of scope are both listed
  • Population/domain/level limits are stated (development, species, culture, task, Marr level)
  • A breakdown regime is named and treated as a test, not a disclaimer
  • (Formal) structural identifiability is discussed; mimicry risk addressed
  • (Formal) parameter recovery is demonstrated by simulation, with degradation noted
  • (Formal) data that would separate the model from a mimicking rival are specified
  • A short "what this theory does not explain" list is included with reasons

Anti-patterns

  • A theory presented as universal, with no stated breakdown condition
  • Boundary conditions written as apologies ("a limitation is...") rather than as theory
  • Skipping identifiability for a model with many free parameters
  • Claiming parameters are meaningful without ever showing they can be recovered
  • Ignoring that a rival model mimics yours on the available data
  • Burying scope limits in a final paragraph instead of theorizing them up front

Output format

【In scope】[phenomena explained]
【Out of scope】[phenomena left to other processes, with reasons]
【Domain limits】[development / species / culture / task / Marr level]
【Breakdown regime】[where the mechanism should stop — stated as a test]
【Identifiability】structural: ok/at-risk | recovery: demonstrated/degraded where [...] | mimicry: [rival], separating data: [...]
【Does NOT explain】[short explicit list]
【Next step】psychrev-conceptual-exhibits (diagram + simulation figures) → psychrev-contribution-framing

© 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 Psychological-Review-Skills/skills/psychrev-boundary-conditions of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

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Manage Settingsasgeirtj/system_prompts_leaks69k—~3.1kAutomated safety check: PassCC0-1.0
Warp Settings Editorwarpdotdev/warp65k1 repos~675Automated safety check: PassAGPL-3.0
Warp Settings Page Builderwarpdotdev/warp65k1 repos~4.5kAutomated safety check: PassAGPL-3.0

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Questions about Psychrev Boundary Conditions

What does Psychrev Boundary Conditions do?

A skill your agent uses when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable. Psychrev Boundary Conditions is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when setting the scope of a Psychological Review theory — what it explains, what it does NOT, and (for formal models) whether its parameters are identifiable.

When should I use Psychrev Boundary Conditions?

Psychrev Boundary Conditions fits situations like: setting the scope of a Psychological Review theory — what it explains; what it does NOT; (for formal models) whether its parameters are identifiable.

How do I install Psychrev Boundary Conditions in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill psychrev-boundary-conditions -a claude-code`. Or copy the skill folder (Psychological-Review-Skills/skills/psychrev-boundary-conditions in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/psychrev-boundary-conditions in your project. Claude Code loads it when a task matches its description.

How do I install Psychrev Boundary Conditions in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill psychrev-boundary-conditions -a codex`. Or copy the skill folder (Psychological-Review-Skills/skills/psychrev-boundary-conditions in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/psychrev-boundary-conditions in your project. Codex loads it when a task matches its description.

Can I use Psychrev Boundary Conditions 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 psychrev-boundary-conditions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/psychrev-boundary-conditions, .gemini/skills/psychrev-boundary-conditions, .github/skills/psychrev-boundary-conditions and .opencode/skills/psychrev-boundary-conditions in your project.

What does Psychrev Boundary Conditions need to run?

SKILL.md names no scripts, command-line tools or credentials: Psychrev Boundary Conditions is instructions for the agent only.

Does Psychrev Boundary Conditions 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 Psychrev Boundary Conditions 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 Psychrev Boundary Conditions use?

Psychrev Boundary Conditions 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 Psychrev Boundary Conditions use?

About 1.1k tokens (SKILL.md is roughly 4.4k 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 Psychrev Boundary Conditions?

Skills that share tags, products or a category with Psychrev Boundary Conditions: Marketing Psychology (nexu-io/open-design, 100k stars), Boundary Setting Scripts (mohitagw15856/pm-claude-skills, 1.4k stars), Manage Settings (asgeirtj/system_prompts_leaks, 69k stars) and Warp Settings Editor (warpdotdev/warp, 65k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Psychrev Boundary Conditions?

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.