Agent skill

Sf Review Process

by franklee16 in franklee16/academic-research-skills

A skill your agent uses to understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne, what expert reviewers weigh (rigor, general significance, theoretical…

No licenceAuto-check passed

Install Sf Review Process

skills CLI
$ npx skills add franklee16/academic-research-skills --skill sf-review-process -a claude-code

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

GitHub CLI
$ gh skill install franklee16/academic-research-skills sf-review-process --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/franklee16/academic-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Awesome-Journal-Skills-main/Social-Forces-Skills/skills/sf-review-process .claude/skills/sf-review-process && 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
sf-review-process
GitHub stars
223
Used in
1 other repo
Token cost
~885 tokens
SKILL.md length
347 words
Files
1
Skills in repo
1,617
Repo updated
First seen
Licence
None found

At a glance

A skill your agent uses to understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne, what expert reviewers weigh (rigor, general significance, theoretical…

  • Works in 5 steps: Double-anonymized. Reviewers do not know… → Editorial screening. The editorial… → Expert external review. Papers that pass… → …
  • Understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne
  • SKILL.md covers When to trigger, How SF review works, Shape the paper to pass and Anti-patterns, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Sf Review Process is an agent skill from franklee16/academic-research-skills. Use to understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne, what expert reviewers weigh (rigor, general significance, theoretical grounding), the typical decision categories, and the journal's reported review timeline. Sets expectations and shapes the paper to survive review; it does not contact editors.

Its SKILL.md is about 890 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: Comprehensive collection of Claude Code skills for academic research in economics, finance, and social sciences.

When your agent uses it

  • Understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne
  • What expert reviewers weigh (rigor
  • General significance
  • Theoretical grounding)

Example prompts

  • “/sf-review-process”

Workflow steps

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

  1. Double-anonymized. Reviewers do not know the authors and authors do not know reviewers.
  2. Editorial screening. The editorial office assesses fit for a general social-science audience
  3. Expert external review. Papers that pass are sent to referees who weigh rigor, identification,
  4. Decision categories: typically reject, revise and resubmit (major/minor), or accept.
  5. Timeline. SF reports a median review-to-decision of ~71 days (a reported metric, not a

What it can do on your machine

Read from SKILL.md and the folder at commit 9a4b2db. 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

Sf Review Process loads about 885 tokens when it runs. Until then it costs about 93 tokens; SKILL.md has 347 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~93
When it runs · the whole SKILL.md, loaded when a task matches
~885

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 347 words (~885 tokens).

“Knowing how Social Forces screens and decides lets you pre-empt the failure modes before submitting. SF is double-anonymized and managed through ScholarOne Manuscript Central for the editorial office at the UNC Department of Sociology. Its reviewers prize methodological rigor, general…”

— opening of SKILL.md by franklee16
name
sf-review-process

Read the full SKILL.md on GitHub

Files

Just SKILL.md in Awesome-Journal-Skills-main/Social-Forces-Skills/skills/sf-review-process of franklee16/academic-research-skills.

Open the folder on GitHubat commit 9a4b2db

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in franklee16/academic-research-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Sf Review Process next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Sf Review Process compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sf Review Process this skillfranklee16/academic-research-skills2231 repos~885Automated safety check: PassNone
Arize Evaluatorgithub/awesome-copilot40k1 repos~8.1kAutomated safety check: NotesMIT
LLM Evaluationdavila7/claude-code-templates33k12 repos~3.5kAutomated safety check: PassMIT
Agent Evaluationsickn33/agentic-awesome-skills47k1 repos~2kAutomated safety check: PassMIT
EvaluatorsArize-ai/phoenix12k—~1.7kAutomated safety check: PassCustom licence
Agent Evaluation Reportingsickn33/agentic-awesome-skills47k1 repos~2.1kAutomated safety check: PassMIT

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Questions about Sf Review Process

What does Sf Review Process do?

A skill your agent uses to understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne, what expert reviewers weigh (rigor, general significance, theoretical…. Sf Review Process is an agent skill from franklee16/academic-research-skills. Use to understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne, what expert reviewers weigh (rigor, general significance, theoretical grounding), the typical decision categories, and the journal's reported review timeline.

When should I use Sf Review Process?

Sf Review Process fits situations like: understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne; what expert reviewers weigh (rigor; general significance; theoretical grounding).

How do I install Sf Review Process in Claude Code?

Run `npx skills add franklee16/academic-research-skills --skill sf-review-process -a claude-code`. Or copy the skill folder (Awesome-Journal-Skills-main/Social-Forces-Skills/skills/sf-review-process in franklee16/academic-research-skills) into .claude/skills/sf-review-process in your project. Claude Code loads it when a task matches its description.

How do I install Sf Review Process in Codex?

Run `npx skills add franklee16/academic-research-skills --skill sf-review-process -a codex`. Or copy the skill folder (Awesome-Journal-Skills-main/Social-Forces-Skills/skills/sf-review-process in franklee16/academic-research-skills) into .agents/skills/sf-review-process in your project. Codex loads it when a task matches its description.

Can I use Sf Review Process 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 franklee16/academic-research-skills --skill sf-review-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sf-review-process, .gemini/skills/sf-review-process, .github/skills/sf-review-process and .opencode/skills/sf-review-process in your project.

What does Sf Review Process need to run?

SKILL.md names no scripts, command-line tools or credentials: Sf Review Process is instructions for the agent only.

Does Sf Review Process 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 Sf Review Process 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 Sf Review Process use?

No licence was found for Sf Review Process or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Sf Review Process use?

About 885 tokens (SKILL.md is roughly 3.5k 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 Sf Review Process?

Skills that share tags, products or a category with Sf Review Process: Arize Evaluator (github/awesome-copilot, 40k stars), LLM Evaluation (davila7/claude-code-templates, 33k stars), Agent Evaluation (sickn33/agentic-awesome-skills, 47k stars) and Evaluators (Arize-ai/phoenix, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sf Review Process?

franklee16 (a GitHub user) maintains it in franklee16/academic-research-skills, which has 223 GitHub stars. The repository holds 1,617 skills in this directory. The repository was last updated on September 18, 2026.

Source: franklee16/academic-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.