Agent skill

Mechanical Engineering Research

by ccplugins in ccplugins/awesome-claude-code-plugins

Research, write, code, analyze, present, and develop proposals for thermal-fluid mechanical engineering work with source-aware rigor.

Apache-2.0Auto-check passedResearch & Science

Install Mechanical Engineering Research

skills CLI
$ npx skills add ccplugins/awesome-claude-code-plugins --skill mechanical-engineering-research -a claude-code

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

GitHub CLI
$ gh skill install ccplugins/awesome-claude-code-plugins mechanical-engineering-research --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/ccplugins/awesome-claude-code-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/thermal-fluid-research-workflow/skills/mechanical-engineering-research .claude/skills/mechanical-engineering-research && 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
mechanical-engineering-research
GitHub stars
968
Token cost
~2.9k tokens
SKILL.md length
1,172 words
Files
12 (incl. references)
Skills in repo
66
Repo updated
First seen
Licence
Apache-2.0

At a glance

Research, write, code, analyze, present, and develop proposals for thermal-fluid mechanical engineering work with source-aware rigor.

  • Works in 5 steps: Clarify the engineering objective. → Build a source hierarchy. → Extract engineering substance. → …
  • Fluid mechanics
  • SKILL.md covers Overview, Workflow Coordination, Research Workflow and Output Patterns, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mechanical Engineering Research is an agent skill from ccplugins/awesome-claude-code-plugins. Research, write, code, analyze, present, and develop proposals for thermal-fluid mechanical engineering work with source-aware rigor. Use for heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, pumps, piping, CFD, experiments, correlations, standards, datasheets, papers, patents, AI/ML tools, computer vision, sequence regression, surrogate modeling, research coding, Overleaf, VS Code, GitHub, git, federal grant proposals, DOE/NSF/NASA-style narratives, invention disclosure…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including reference files (for example `agents/openai.yaml`, `references/ai-tools-thermal-fluids.md` and `references/brief-template.md`).

It sits in Research & Science, covering Intellectual property, Physical and earth sciences and Proposals and quotes. It works with Git, GitHub and Visual Studio Code. The repository describes itself as: Awesome Claude Code plugins — a curated list of slash commands, subagents, MCP servers, and hooks for Claude Code. The licence is Apache-2.0.

When your agent uses it

  • Fluid mechanics
  • Computer vision
  • Sequence regression
  • Surrogate modeling

Example prompts

  • “/mechanical-engineering-research”

Workflow steps

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

  1. Clarify the engineering objective.
  2. Build a source hierarchy.
  3. Extract engineering substance.
  4. Compare alternatives by mechanism.
  5. Produce a decision-ready output.

What it can do on your machine

Read from SKILL.md and the folder at commit 5bd4f16. 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

Mechanical Engineering Research loads about 2.9k tokens when it runs, and up to ~28k if it reads all its reference files. Until then it costs about 239 tokens; SKILL.md has 1,172 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~239
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~28k

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 ccplugins/awesome-claude-code-plugins at commit 5bd4f16, republished under its Apache-2.0 licence (© ccplugins). 1,172 words, ~2,889 tokens.

Download SKILL.mdSave it as .claude/skills/mechanical-engineering-research/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
mechanical-engineering-research
description
Research, write, code, analyze, present, and develop proposals for thermal-fluid mechanical engineering work with source-aware rigor. Use for heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, pumps, piping, CFD, experiments, correlations, standards, datasheets, papers, patents, AI/ML tools, computer vision, sequence regression, surrogate modeling, research coding, Overleaf, VS Code, GitHub, git, federal grant proposals, DOE/NSF/NASA-style narratives, invention disclosure, provisional patent support, commercialization, and trade studies. Produces technical briefs, critical literature reviews, proposal narratives, review-criteria responses, manuscript sections, methods, results discussions, data-analysis plans, plots, presentations, design comparisons, calculation plans, reproducible code, repository workflows, disclosure drafts, patent-support packets, and research roadmaps.

Mechanical Engineering Research

Overview

Use this skill to research thermal-fluid systems with engineering rigor: define the question, collect reliable sources, preserve assumptions and validity ranges, and separate verified evidence from inference.

Workflow Coordination

For full paper, proposal, review-article, thesis chapter, or major manuscript workflows, use an academic-research workflow as the scaffold when one is available, and use this skill as the thermal-fluid/mechanical-engineering judgment layer.

Treat the roles as:

  • Academic research workflow: organize the process, checkpoints, outline, drafting sequence, review/revision loop, citation/claim checks, and finalization.
  • Mechanical engineering research skill: enforce domain logic, physical reasoning, literature synthesis standards, methodology detail, assumptions, data-analysis rigor, figure discussion, plotting, presentation quality, AI/ML interpretation, reproducible coding, and proposal-specific technical judgment.

When both are available, do not let a generic academic workflow overwrite domain judgment. Apply this skill whenever deciding whether the research question, gap, method, DOE, model assumptions, interpretation, figure narrative, or proposal significance is mechanically and thermally sound.

Research Workflow

  1. Clarify the engineering objective.

    • Identify the system, working fluid, operating regime, geometry, boundary conditions, performance metric, and constraints.
    • Ask for missing high-impact values only when they determine the research path; otherwise state assumptions and proceed.
  2. Build a source hierarchy.

    • Prefer standards, textbooks/handbooks, peer-reviewed papers, manufacturer datasheets, government or lab reports, and primary patents.
    • Use web search for current papers, standards status, products, prices, regulations, or citations. Cite sources with links whenever browsing is used.
    • Treat blogs, marketing pages, forum posts, and uncited summaries as orientation only unless the user explicitly asks for informal context.
  3. Extract engineering substance.

    • Capture equations, correlations, dimensionless groups, material limits, empirical constants, and uncertainty.
    • Record applicability limits: Reynolds/Rayleigh/Nusselt ranges, Prandtl range, Mach/compressibility assumptions, phase-change regime, geometry, roughness, orientation, temperature/pressure range, and fluid property source.
    • Note what was measured, simulated, or assumed.
  4. Compare alternatives by mechanism.

    • Explain why each design or model performs differently, not only which is "best."
    • Consider pressure drop, heat-transfer coefficient, pumping power, fouling, manufacturability, instrumentation, maintenance, safety, cost, and scaling behavior.
  5. Produce a decision-ready output.

    • Lead with the answer or recommendation.
    • Include assumptions, key evidence, equations/correlations, source quality, uncertainty, and next verification steps.
    • Mark engineering inference explicitly when sources do not directly prove a claim.
    • Use a clear paragraph logic flow: each paragraph starts with a central topic sentence, and each following sentence develops, supports, qualifies, or transitions from that topic.

Output Patterns

For a research brief, use:

  • Question: One sentence defining the engineering problem.
  • Bottom Line: Concise answer, recommendation, or state of evidence.
  • Assumptions: Operating conditions, geometry, fluid, and scope.
  • Evidence: Source-backed findings with citations.
  • Models/Correlations: Equations, variables, units, and validity limits.
  • Tradeoffs: Performance, cost, safety, reliability, manufacturability, and uncertainty.
  • Gaps: What remains unverified or standards-dependent.
  • Next Steps: Calculations, experiments, simulations, or standards lookups.

For a literature review, read references/literature-review.md. Group sources by mechanism, method, design family, or unresolved question rather than listing papers chronologically.

For federal research proposals, DOE EPSCoR/National Laboratory partnership proposals, full narrative expansions, review-criteria responses, proposal figure planning, preliminary-results integration, or ready-to-submit proposal polishing, read references/proposal-development.md.

For a design comparison, include a compact decision matrix and explain the dominant physics behind each score.

For manuscript-style technical writing, read references/technical-writing-analysis.md before drafting or revising introductions, methods, modeling sections, results/discussion, data analysis, or plot narratives.

For full technical papers, journal manuscripts, or paper-style section drafting, also read references/paper-writing-style.md to match the preferred section logic, abstract style, figure-led results, and conclusion patterns.

For experiments, simulations, or parameter studies, use references/technical-writing-analysis.md to plan a detailed baseline case and hypothesis-driven DOE before proposing broad sweeps or large case matrices.

For research presentations or slide decks, read references/presentation-slides.md before creating slide outlines, slide content, speaker notes, or visual-story plans.

For AI/ML-assisted thermal-fluid research, read references/ai-tools-thermal-fluids.md before recommending computer vision, sequence regression, surrogate modeling, sensor fusion, dimensionality reduction, or data-driven control workflows.

For research code, scripts, notebooks, data pipelines, plotting code, CFD automation, or ML implementation, read references/research-coding.md before writing or reviewing code.

For research tool workflows involving Overleaf, VS Code, GitHub, or git, read references/research-toolchain.md before advising on manuscript collaboration, code/debugging workflow, repository updates, archival releases, branches, commits, tags, or reproducibility hygiene.

For innovation, invention disclosure, provisional patent support, utility patent technical content, or technology commercialization, read references/innovation-commercialization.md before drafting disclosure answers, non-confidential summaries, technical descriptions, figure lists, prior-art comparisons, market/use-case notes, inventor response emails, or commercialization briefs. Support the technical and strategic content, but do not provide legal advice; defer claim scope, filing strategy, assignments, declarations, and prosecution decisions to Technology Ventures and patent counsel.

Show full SKILL.md (430 more words)Show less

Thermal-Fluid Checks

Before finalizing, check whether the answer should account for:

  • Laminar, transitional, turbulent, natural, forced, or mixed convection.
  • Internal, external, developing, fully developed, compressible, multiphase, or non-Newtonian flow.
  • Radiation, conduction contact resistance, fins, heat pipes, boiling, condensation, or evaporative cooling.
  • Pump/fan curves, NPSH, cavitation, choking, surge, fouling, erosion, corrosion, thermal stress, or fatigue.
  • Property variation with temperature and pressure.
  • Similarity/scaling limits between benchtop tests, CFD, and full-scale systems.
  • Applicable ASME, ASTM, ISO, API, ASHRAE, NFPA, or local code requirements.

CFD And Experiments

When discussing CFD:

  • Identify turbulence model, wall treatment, mesh independence, boundary conditions, property models, convergence criteria, and validation data.
  • Do not present CFD as evidence unless the setup and validation are known.
  • Suggest simpler analytical or empirical checks as sanity bounds when available.

When discussing experiments:

  • Identify sensors, calibration, uncertainty, repeatability, heat loss correction, flow development, and property measurement.
  • Prefer outputs that can be independently reproduced from stated dimensions and conditions.

Reference Files

Read references/brief-template.md when the user asks for a reusable research brief format, report outline, or deliverable template.

Read references/technical-writing-analysis.md when the user asks for technical writing, manuscript sections, data analysis, figures, plots, or results discussion.

Read references/paper-writing-style.md when the user asks to write, revise, outline, or polish a journal paper, conference paper, manuscript, abstract, introduction, methods, results/discussion, conclusion, or paper-style technical narrative.

Read references/literature-review.md when the user asks for a literature review, related-work section, research background, citation map, state-of-the-art comparison, review figure/table, future-work analysis, or paper discovery strategy.

Read references/proposal-development.md when the user asks for grant/proposal development, solicitation alignment, pre-application expansion, DOE EPSCoR or National Lab partnership narratives, collaborator document planning, review-criteria mapping, milestones, preliminary-results integration, proposal figures, reviewer-friction diagnosis, references, or ready-to-submit polish.

Read references/presentation-slides.md when the user asks for presentation slides, a research talk, conference talk, group-meeting slides, slide-by-slide narrative, speaker notes, animation/video suggestions, or figure-focused storytelling.

Read references/ai-tools-thermal-fluids.md when the user asks about AI tools, machine learning, computer vision, BubbleID, SeqReg, CFDTwin, DataDroid-LAM, MEEG-54403, sensor fusion, surrogate modeling, dimensionality reduction, thermal-fluid datasets, or ML-enhanced data analysis.

Read references/research-coding.md when the user asks for coding help, research scripts, notebooks, data processing, plotting, reproducibility, simulation automation, CFD post-processing, ML implementation, repository organization, or code review.

Read references/research-toolchain.md when the user asks about Overleaf writing/editing, VS Code coding/debugging, GitHub repo updating or archiving, git branches/commits/tags/releases, repository hygiene, manuscript-code-data synchronization, or reproducible project handoff.

Read references/innovation-commercialization.md when the user asks for invention disclosure, Technology Ventures, Sophia disclosure, provisional patent, utility patent application support, patent counsel feedback, USPTO filing support, notice of allowance/grant tracking, licensing, startup/commercialization strategy, non-confidential summaries, or translating research results into protectable/commercializable technology.

© ccplugins, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (references) in plugins/thermal-fluid-research-workflow/skills/mechanical-engineering-research of ccplugins/awesome-claude-code-plugins.

  • SKILL.md
  • agents/openai.yaml
  • references/ai-tools-thermal-fluids.md
  • references/brief-template.md
  • references/innovation-commercialization.md
  • references/literature-review.md
  • references/paper-writing-style.md
  • references/presentation-slides.md
  • references/proposal-development.md
  • references/research-coding.md
  • references/research-toolchain.md
  • references/technical-writing-analysis.md

Open the folder on GitHubat commit 5bd4f16

Compare with similar skills

Mechanical Engineering Research 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.

Mechanical Engineering Research compared with similar skills
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Denariodavila7/claude-code-templates32k9 repos~1.5kAutomated safety check: NotesMIT
Open-Source Release Readinesstrailofbits/skills7.4k—~2.6kAutomated safety check: PassCC-BY-SA-4.0
Sciatlas Idea Groundingzjunlp/SciAtlas160—~1.1kAutomated safety check: PassMIT
Aminer MCP ResearchDrchronx/ai-agent-research-starter-kit135—~1.1kAutomated safety check: PassCustom licence

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Questions about Mechanical Engineering Research

What does Mechanical Engineering Research do?

Research, write, code, analyze, present, and develop proposals for thermal-fluid mechanical engineering work with source-aware rigor. Mechanical Engineering Research is an agent skill from ccplugins/awesome-claude-code-plugins. Research, write, code, analyze, present, and develop proposals for thermal-fluid mechanical engineering work with source-aware rigor.

When should I use Mechanical Engineering Research?

Mechanical Engineering Research fits situations like: fluid mechanics; computer vision; sequence regression; surrogate modeling.

How do I install Mechanical Engineering Research in Claude Code?

Run `npx skills add ccplugins/awesome-claude-code-plugins --skill mechanical-engineering-research -a claude-code`. Or copy the skill folder (plugins/thermal-fluid-research-workflow/skills/mechanical-engineering-research in ccplugins/awesome-claude-code-plugins) into .claude/skills/mechanical-engineering-research in your project. Claude Code loads it when a task matches its description.

How do I install Mechanical Engineering Research in Codex?

Run `npx skills add ccplugins/awesome-claude-code-plugins --skill mechanical-engineering-research -a codex`. Or copy the skill folder (plugins/thermal-fluid-research-workflow/skills/mechanical-engineering-research in ccplugins/awesome-claude-code-plugins) into .agents/skills/mechanical-engineering-research in your project. Codex loads it when a task matches its description.

Can I use Mechanical Engineering Research 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 ccplugins/awesome-claude-code-plugins --skill mechanical-engineering-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mechanical-engineering-research, .gemini/skills/mechanical-engineering-research, .github/skills/mechanical-engineering-research and .opencode/skills/mechanical-engineering-research in your project.

What does Mechanical Engineering Research need to run?

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

Does Mechanical Engineering Research 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 Mechanical Engineering Research 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 Mechanical Engineering Research use?

Mechanical Engineering Research is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Mechanical Engineering Research use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 25k tokens, read only when the agent opens those files.

What are the alternatives to Mechanical Engineering Research?

Skills that share tags, products or a category with Mechanical Engineering Research: Mechanical Engineering Research (hashgraph-online/awesome-codex-plugins, 1.2k stars), Denario (davila7/claude-code-templates, 32k stars), Open-Source Release Readiness (trailofbits/skills, 7.4k stars) and Sciatlas Idea Grounding (zjunlp/SciAtlas, 160 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mechanical Engineering Research?

ccplugins (a GitHub organization) maintains it in ccplugins/awesome-claude-code-plugins, which has 968 GitHub stars. The repository holds 66 skills in this directory. The repository was last updated on August 12, 2026.

Source: ccplugins/awesome-claude-code-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.