Agent skill

Transportation Research Part B Methodological

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

A skill your agent uses when targeting Transportation Research Part B (Methodological) or deciding whether a transportation manuscript fits this venue.

MITAuto-check passed

Install Transportation Research Part B Methodological

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill transportation-research-part-b-methodological -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills transportation-research-part-b-methodological --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/Engineering-Technology-Journal-Skills/skills/transportation-research-part-b-methodological .claude/skills/transportation-research-part-b-methodological && 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
transportation-research-part-b-methodological
GitHub stars
1.2k
Token cost
~2.1k tokens
SKILL.md length
897 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when targeting Transportation Research Part B (Methodological) or deciding whether a transportation manuscript fits this venue.

  • Targeting Transportation Research Part B (Methodological)
  • SKILL.md covers Journal positioning, When to trigger, Scope & topic fit and Method & evidence bar, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Deciding whether a transportation manuscript fits this venue

What it does

Transportation Research Part B Methodological is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when targeting Transportation Research Part B (Methodological) or deciding whether a transportation manuscript fits this venue. Encodes the journal's methodological-flagship fit, the theoretical-contribution bar, the Part B vs. Part A/C/E routing, modeling-and-proof rigor, house style, official-submission re-check, and desk-reject heuristics.

Its SKILL.md is about 2.1k 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

  • Targeting Transportation Research Part B (Methodological)
  • Deciding whether a transportation manuscript fits this venue

Example prompts

  • “/transportation-research-part-b-methodological”

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

Transportation Research Part B Methodological loads about 2.1k tokens when it runs. Until then it costs about 99 tokens; SKILL.md has 897 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

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). 897 words, ~2,129 tokens.

Download SKILL.mdSave it as .claude/skills/transportation-research-part-b-methodological/SKILL.md (or your agent's skills folder).
name
transportation-research-part-b-methodological
description
Use when targeting Transportation Research Part B (Methodological) or deciding whether a transportation manuscript fits this venue. Encodes the journal's methodological-flagship fit, the theoretical-contribution bar, the Part B vs. Part A/C/E routing, modeling-and-proof rigor, house style, official-submission re-check, and desk-reject heuristics.

Transportation Research Part B: Methodological (transportation-research-part-b-methodological)

Journal positioning

Transportation Research Part B (Methodological) is the Elsevier methodological flagship of the transportation research family, publishing work whose primary contribution is a methodological or theoretical advance in transportation modeling and analysis: traffic flow theory, network equilibrium and traffic assignment, transportation network design and optimization, travel-demand and discrete-choice modeling, transport economics methods, and freight/logistics modeling. The defining expectation is a generalizable method, model, or theorem — a new formulation, a proven property, a new estimator or algorithm with analytical justification — not an applied case study that uses existing methods. A well-executed empirical application with no methodological novelty belongs in Part A; this skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current official author guidelines. Before submitting, re-check the live Transportation Research Part B Guide for Authors.

When to trigger

  • The author names Part B for a transportation modeling, network, choice, or transport-economics manuscript and wants a fit/framing check.
  • A paper must be re-framed from "we applied a model to this city/dataset" into a generalizable methodological contribution with analytical results.
  • The author is deciding among Part B (methodological), Part A (policy/behavior), Part C (emerging technologies), and Part E (logistics/transportation economics applications).
  • The author needs Part B's modeling-rigor and proof expectations and its desk-reject heuristics.

Scope & topic fit

  • Traffic flow theory: kinematic-wave and car-following models, macroscopic fundamental diagrams, network loading, with new analytical or modeling results.
  • Network equilibrium and traffic assignment: user/system equilibrium, dynamic traffic assignment, existence/uniqueness and convergence properties.
  • Transportation network design and optimization: bilevel/robust/stochastic formulations, exact and approximation algorithms with performance guarantees.
  • Travel-demand and discrete-choice modeling: new model structures, identification and estimation theory, behavioral econometrics for transportation.
  • Transport economics methods: congestion pricing, capacity and investment theory, mechanism design — when the contribution is methodological, not a policy case.
  • Freight, logistics, and supply-chain modeling when the advance is a formulation, algorithm, or analytical property rather than an industry case study.

Method & evidence bar

  • The central object is a method, model, or theorem with a clear, generalizable contribution; analytical results (existence, uniqueness, optimality, convergence, identification) are stated and proven where claimed.
  • Assumptions must be explicit and reasonable; a result that holds only under assumptions that trivialize the problem is not a contribution.
  • Algorithms require complexity or convergence analysis, or rigorous computational evidence on benchmark instances, not a single illustrative run.
  • Econometric/choice contributions must address identification and estimation properties, not merely report coefficient estimates from one dataset.
  • Numerical experiments validate and illustrate the method; they support but never substitute for the analytical contribution.
  • Position precisely against the closest prior models/theorems: state what is new (weaker assumptions, broader network class, tighter bound, new identification).

Structure & house style

  • Standard methodological-article structure: precise problem formulation, model/method development, analytical results (propositions/theorems with proofs), and numerical experiments; Part B publishes full-length methodological articles, so route applied or short pieces elsewhere and re-check current article types on the live guide.
  • The introduction motivates the methodological gap in the transportation literature, not the policy importance of a corridor or city.
  • Notation must be standard and consistent; the formulation is stated precisely before any result, and proofs appear in-text or in an appendix per current rules.
  • Figures and tables serve the method (convergence plots, sensitivity to network size, benchmark comparisons); the paper stands on its formulation and results.
  • Supplementary/appendix material carries long proofs and full computational details per the current policy.
Show full SKILL.md (337 more words)Show less

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the Elsevier anchors, then cite the current Transportation Research Part B Guide for Authors page you checked.
  • Search the live site for "Transportation Research Part B guide for authors" and follow the current Elsevier/Editorial Manager version; confirm you are targeting Part B (Methodological), not Part A/C/E.
  • Re-check article types, length expectations, and structured-abstract or highlights requirements if applicable.
  • Confirm data/code availability expectations for numerical experiments and any benchmark-instance sharing policy.
  • Re-check competing-interests, funding, author-contribution (CRediT), and AI-use disclosure requirements.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • The contribution is a generalizable method/model/theorem, not an application of existing methods to one dataset.
  • Every analytical claim (existence/uniqueness/optimality/convergence/identification) has a complete, correct proof or rigorous justification.
  • Assumptions are explicit and non-trivializing, and the result's scope is clearly delimited.
  • Novelty is pinned to specific prior models/theorems (weaker assumptions / broader class / tighter bound / new identification).
  • Numerical experiments illustrate and validate but do not substitute for the analytical contribution.
  • The paper targets Part B specifically, not Part A/C/E, and notation/formulation is precise.

Common desk-reject triggers

  • An applied case study that uses existing models with no methodological advance (a Part A fit).
  • An algorithm with no complexity/convergence analysis and only a single illustrative run.
  • A choice/econometric model reporting estimates from one dataset with no identification or estimation contribution.
  • Results stated without proofs, or proofs that are incomplete, incorrect, or rely on trivializing assumptions.
  • Scope mismatch: a pure operations-research, pure machine-learning, or technology-deployment paper with transportation only as a label.
  • Better framed for the technology-focused Part C or the logistics-applications Part E.

Re-routing decision

  • Policy, behavior, or empirical analysis without methodological novelty → Transportation Research Part A.
  • Emerging-technology / sensing / data-driven ITS focus → Transportation Research Part C.
  • Logistics and transportation-economics applications → Transportation Research Part E.
  • Network optimization with no transportation object as the core → a dedicated operations-research venue.
  • General methodological breadth beyond this bundle → consult the natural-science routing slugs only if scope truly leaves engineering.

Output format

text
[Fit] High / Medium / Low (one-line reason)
[Target] Transportation Research Part B (Methodological)
[Topic tags] <2–3 closest methodological subtopics>
[Contribution type] new model / formulation / theorem / estimator / algorithm
[Method/evidence] <does it clear the generality + analytical-rigor bar, or is it an application?>
[Top risk] <the single most likely reason for rejection>
[Part check] B vs. A vs. C vs. E
[Official items to re-check] <article type / length / data-code / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>

© 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 Engineering-Technology-Journal-Skills/skills/transportation-research-part-b-methodological of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

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Questions about Transportation Research Part B Methodological

What does Transportation Research Part B Methodological do?

A skill your agent uses when targeting Transportation Research Part B (Methodological) or deciding whether a transportation manuscript fits this venue. Transportation Research Part B Methodological is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when targeting Transportation Research Part B (Methodological) or deciding whether a transportation manuscript fits this venue.

When should I use Transportation Research Part B Methodological?

Transportation Research Part B Methodological fits situations like: targeting Transportation Research Part B (Methodological); deciding whether a transportation manuscript fits this venue.

How do I install Transportation Research Part B Methodological in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill transportation-research-part-b-methodological -a claude-code`. Or copy the skill folder (Engineering-Technology-Journal-Skills/skills/transportation-research-part-b-methodological in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/transportation-research-part-b-methodological in your project. Claude Code loads it when a task matches its description.

How do I install Transportation Research Part B Methodological in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill transportation-research-part-b-methodological -a codex`. Or copy the skill folder (Engineering-Technology-Journal-Skills/skills/transportation-research-part-b-methodological in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/transportation-research-part-b-methodological in your project. Codex loads it when a task matches its description.

Can I use Transportation Research Part B Methodological 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 transportation-research-part-b-methodological -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/transportation-research-part-b-methodological, .gemini/skills/transportation-research-part-b-methodological, .github/skills/transportation-research-part-b-methodological and .opencode/skills/transportation-research-part-b-methodological in your project.

What does Transportation Research Part B Methodological need to run?

SKILL.md names no scripts, command-line tools or credentials: Transportation Research Part B Methodological is instructions for the agent only.

Does Transportation Research Part B Methodological 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 Transportation Research Part B Methodological 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 Transportation Research Part B Methodological use?

Transportation Research Part B Methodological 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 Transportation Research Part B Methodological use?

About 2.1k tokens (SKILL.md is roughly 8.5k 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 Transportation Research Part B Methodological?

Skills that share tags, products or a category with Transportation Research Part B Methodological: Benchmark Methodology (affaan-m/ECC, 277k stars), Bb Methodology (sickn33/agentic-awesome-skills, 47k stars), Evaluation Methodology (wshobson/agents, 40k stars) and Step Parts (earthtojake/text-to-cad, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Transportation Research Part B Methodological?

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.