compare
Skill10 starsChanged 4 days agoMITView on GitHub
Compare multiple engineering sources on a question — standards, code provisions, design alternatives, products, methods, datasheets — and produce a source-grounded comparison matrix of agreements, disagreements, and confidence. Use when the user asks to compare standards, weigh design options, choose between products or methods, or see where sources disagree.
16 other projects use a version of this.
Adopted by
Most recently taken up by
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tooltheir own version, first seen Nov 8, 2026
- synaptiai/agent-capability-standardtheir own version, first seen Nov 1, 2026
- Hainrixz/claude-seo-aitheir own version, first seen Nov 1, 2026
- ansvisor/ansvisortheir own version, first seen Nov 1, 2026
- TakaGoto/rag-learning-academytheir own version, first seen Oct 28, 2026
- harshil-1411/claude_plugin_video_studiotheir own version, first seen Oct 17, 2026
Used with
Projects with it also use evaluate, create and 6 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
NVIDIASkillevaluate
Scores existing Sports Intelligence AVLM inference outputs with avlm/evals: MCQ accuracy (run_mcq_eval.sh, INFERENCE_DIR), open-ended LLM-as-judge scores (needs CLIENT_API_KEY for the configured judge endpoint), tennis category breakdowns, run comparisons, chance-level sanity checks and triage of mcq_results.json or llm_judge_results.json. Use when the user asks to score, evaluate, benchmark or compare predictions.jsonl from inference runs, or to explain a suspicious accuracy. Not for running inference, training, quantization, data preparation, or third-party API model inference: never open, list or run anything under avlm/evals/inference_3rdparty, including when the user asks for it; it is excluded from the release.
Also in 3 projects that use this
MicrosoftSkillcreate
Also in 3 projects that use this
aakash-dharSkilloptimize
Analyzes code for performance issues including slow algorithms, memory leaks, unnecessary re-renders, database query problems, and resource bottlenecks. Use when the user says "this is slow", "optimize this", "performance issue", "why is this taking so long?", or "make this faster".
Also in 4 projects that use this
AnthropicSkillanalyze
Answer data questions -- from quick lookups to full analyses. Use when looking up a single metric, investigating what's driving a trend or drop, comparing segments over time, or preparing a formal data report for stakeholders.
Also in 3 projects that use this
- MicrosoftSkill
report
Turn an exploration (threads, findings, charts) into a single Markdown report — note, blog post, executive summary, KPI dashboard, slide brief, or multi-section analytical report, with embedded charts.
Also in 3 projects that use this
- AnthropicSkill
start
Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.
Also in 3 projects that use this
Other versions16 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 16
- andrew-shwetzer/career-ops-plugin★ 501same name
- andrew-shwetzer/career-ops-plugin-do-not-fork-currently-updating-v2-★ 500same name
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool★ 432same name
- ansvisor/ansvisor★ 233same name
- Hainrixz/claude-seo-ai★ 81same name
- TakaGoto/rag-learning-academy★ 24same name
- n24q02m/wet★ 23same name
- n24q02m/wet-mcp★ 23same name
- joyehuang/skills★ 9same name
- yarikleto/claude-teacher-plugin★ 9same name
6 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository28 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- architecturalSkill
- artifact-readingSkill
- auditSkill
- civilSkill
- design-alternativesSkill
- electricalSkill
- eli5Skill
- engineering-researchSkill
- evidence-rankingSkill
- fmea-brainstormSkill
- gap-analysisSkill
- habitSkill
- hypothesis-generationSkill
- mechanicalSkill
- peer-reviewSkill
- proposalSkill
- research-to-postSkill
- reviewSkill
- scholarly-researchSkill
- simplified-technical-englishSkill
- softwareSkill
- standards-lookupSkill
- summarizeSkill
- verifierSkill
- vitruvius-helpSkill
- vitruviusSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 15 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 20
Run the shared /skill:engineering-research method with this deliverable shape.
- Distinctive: line 25
Before searching, name the question, the artifact/scope (or say it is a literature review), the jurisdiction/edition, and the effort budget …
“Common” is measured: kept by at least 6 in 10 of the 15 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- VITRUVIUS-COMPILED-SKILL:BEGIN v1 sha256=fec76b68b95b67b2f2cb6933afa9549b5aa73e8a15cc2a197a32780f9014a498 -->Engineering Source Comparison
Run the shared /skill:engineering-research method with this deliverable
shape. Do not restate the research loop here.
Input Gate
Before searching, name the question, the artifact/scope (or say it is a
literature review), the jurisdiction/edition, and the effort budget (user-set or
thorough). Ask ONE clarifying question if the ask is too vague, then proceed.
See references/input-gate.md.
Workflow
- Plan — name the comparison set, the dimensions to evaluate, and the
expected matrix columns. Write
outputs/.plans/<slug>.md. Get user confirmation before gathering. - Scale — direct search for 2–3 items; a
researchersubagent only for a broad set (4+ items or multi-source). - Gather — use the discipline lens's evidence landscape. Read each source directly before describing it; record standard + section + edition.
- Build the matrix — one row per item, columns covering:
- source (standard/URL/artifact, with section + edition)
- key claims or provisions
- evidence type (code / datasheet / test / field / secondary)
- caveats
- confidence (
verified,inferred,blocked)
- Cite — inline citations
[1],[2]; verify every source means what it claims. Distinguish agreement, disagreement, and uncertainty clearly. - Review — run the adversarial pass; fix FATAL issues.
Output
Save exactly one comparison to outputs/<slug>-comparison.md, ending with a
Sources section of standard + section, URLs, and artifact paths for every
row. For each disagreement between sources, state which is newer, which is
jurisdiction/application-specific, and what a decision-maker should weigh.
Scope and Boundaries
- This skill produces research — it does NOT produce final designs or construction documents.
- Research-only, not for final engineering sign-off. Licensed engineers must review and approve any design based on this research.
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