compare
Skill9 starsChanged 2 months agoMITView on GitHub
Use when the student wants a structured side-by-side comparison of two concepts — creates a researched comparison table, usage scenarios, misconceptions, and key takeaway adapted to the student's level
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
- adeerkhan/vitruviustheir own version, first seen Oct 20, 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
OpenAISkillaudit
Audit or critique a product flow, journey, workflow, funnel, onboarding path, checkout path, settings path, screen, or multi-step product experience by capturing screenshots first, then reporting UX, design, and accessibility findings inline from that evidence. Use Figma only when the user explicitly asks for a board. Use when the user asks to audit, review, critique, inspect, assess, analyze, evaluate, or give feedback on a product experience.
Also in 6 projects that use this
MicrosoftSkillreport
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
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
- adeerkhan/vitruvius★ 10same name
- joyehuang/skills★ 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 repository15 other files it gives its agents.
- .claude/CLAUDE.mdCLAUDE.md
- asciiSkill
- challengeSkill
- demoSkill
- excalidrawSkill
- flashcardsSkill
- init-eduSkill
- motivateSkill
- progressSkill
- quiz-meSkill
- researchSkill
- reset-eduSkill
- roadmapSkill
- save-progressSkill
- summarySkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
17 rules. 0 are common, 8 are distinctive, and 9 are very specific to this project.
0
Common
Most of the 15 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
9
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 9
Before accessing education data, read ${CLAUDE_PLUGIN_ROOT}/references/education-data.md.
- Very specific: line 29
Read <education-db>/student.json — adapt to level, interests, and learning style
- Very specific: line 30
Read <education-db>/dashboard.json — check if either concept is already tracked
- Very specific: line 31
If tracked, read <education-db>/topics/<concept>.json for each — check depth, misconceptions
- Distinctive: line 32
Use WebSearch to research BOTH concepts: before writing the comparison — never rely solely on training data.
- Distinctive: line 93
Always research first: Use WebSearch for both concepts before writing.
- Very specific: line 94
Adapt to student level: Read student.json:
- Distinctive: line 98
Use the student's interests for analogies: If they like gaming, music, sports — weave those into the "when to use which" scenarios or the …
- Distinctive: line 99
Respect dislikes: If the student dislikes dry textbook comparisons, lead with real-world scenarios.
- Distinctive: line 100
Address known misconceptions first: If either concept has unresolved misconceptions in its topic file, the "Common misconceptions" section …
- Distinctive: line 101
Keep the table scannable: Use short values in table cells.
- Distinctive: line 102
Be honest about overlap: If the concepts are not strictly either/or (e.g., "you can use both together"), say so clearly.
- Distinctive: line 113
After generating the comparison:
- Very specific: line 126
Update only last_seen to today
- Very specific: line 127
Add the other concept to related_topics if not already present
- Very specific: line 131
Update last_seen for any tracked concepts
- Very specific: line 132
If either concept is new and has not been covered before, do NOT create a topic entry — comparisons alone are not enough to mark a topic as …
“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
Requested topic/task: $ARGUMENTS
Before accessing education data, read ${CLAUDE_PLUGIN_ROOT}/references/education-data.md. Resolve every <education-db> below using that contract. Current session ID: ${CLAUDE_SESSION_ID}.
Compare — Side-by-Side Concept Comparisons
Creates a structured, researched comparison of two concepts. Adapts depth and language to the student's level. Results are saved to both project-local and global education docs.
Invocation
/claude-teacher:compare <concept A> vs <concept B>
Examples:
/claude-teacher:compare TCP vs UDP/claude-teacher:compare REST vs GraphQL/claude-teacher:compare mutex vs semaphore/claude-teacher:compare Docker vs VMs/claude-teacher:compare SQL vs NoSQL
Process
- Parse the two concepts from the invocation (prefer
vsorversus; ask if the boundary is ambiguous instead of splitting names that containand) - Read
<education-db>/student.json— adapt to level, interests, and learning style - Read
<education-db>/dashboard.json— check if either concept is already tracked - If tracked, read
<education-db>/topics/<concept>.jsonfor each — check depth, misconceptions - Use WebSearch to research BOTH concepts before writing the comparison — never rely solely on training data. Search for official documentation, authoritative articles, and recent best-practice guides for each concept.
- Generate the structured comparison (see Output Format below)
- Save comparison to docs and update DB (see DB Update below)
Output Format
Present the comparison in this exact structure:
── Compare: [Concept A] vs [Concept B] ──────────────────
## What they are
**[Concept A]:** [One-line summary]
**[Concept B]:** [One-line summary]
## Side-by-side comparison
| Feature | [Concept A] | [Concept B] |
|--------------------|-------------------|-------------------|
| [Feature 1] | [Value/behavior] | [Value/behavior] |
| [Feature 2] | [Value/behavior] | [Value/behavior] |
| [Feature 3] | [Value/behavior] | [Value/behavior] |
| ... | ... | ... |
Include 5-8 rows covering the most important differentiators.
Adapt column detail to student level (beginner = simpler terms, advanced = precise technical language).
## When to use which
**Choose [Concept A] when:**
- [Concrete scenario 1]
- [Concrete scenario 2]
- [Concrete scenario 3]
**Choose [Concept B] when:**
- [Concrete scenario 1]
- [Concrete scenario 2]
- [Concrete scenario 3]
## Common misconceptions
- **Misconception:** "[common wrong belief]"
**Reality:** [correction with explanation]
- **Misconception:** "[another common wrong belief]"
**Reality:** [correction with explanation]
Include 2-4 misconceptions. If the student has recorded misconceptions about either topic, address those FIRST.
## Key takeaway
> [One memorable sentence that captures the essential difference]
**Sources:** [list 2-4 links to official docs, RFCs, or authoritative articles used]
──────────────────────────────────────────────────────────Rules
- Always research first. Use WebSearch for both concepts before writing. Every factual claim must be backed by a source. List sources at the end.
- Adapt to student level. Read
student.json:- Beginner: use analogies from their interests, simpler terms, fewer rows in the table
- Intermediate: balance precision with clarity, include practical examples
- Advanced: use precise technical language, include edge cases and nuances
- Use the student's interests for analogies. If they like gaming, music, sports — weave those into the "when to use which" scenarios or the key takeaway.
- Respect dislikes. If the student dislikes dry textbook comparisons, lead with real-world scenarios. If they dislike oversimplification, include nuanced details.
- Address known misconceptions first. If either concept has unresolved misconceptions in its topic file, the "Common misconceptions" section must address those before generic ones.
- Keep the table scannable. Use short values in table cells. If a cell needs elaboration, add a footnote below the table.
- Be honest about overlap. If the concepts are not strictly either/or (e.g., "you can use both together"), say so clearly.
- After the comparison, suggest next steps:
Want to go deeper? - /claude-teacher:ascii [concept] — visualize how each works under the hood - /claude-teacher:quiz-me [concept] — test your understanding of either concept - /claude-teacher:challenge [concept] — hands-on practice with one of them
DB Update
After generating the comparison:
1. Save comparison doc to both locations:
- Global:
<education-db>/docs/<concept-a>-vs-<concept-b>.md - Project-local:
docs/<concept-a>-vs-<concept-b>.md(ifdocs/directory exists in the project)
Each saved doc includes:
- The full comparison output
- Sources/links used
- Date saved
- Related topics
2. Update topic files — for each concept that exists in <education-db>/topics/:
- Update only
last_seento today - Add the other concept to
related_topicsif not already present - Preserve
last_reviewed,next_review, andreview_interval_daysuntil an assessment
3. Update dashboard <education-db>/dashboard.json:
- Update
last_seenfor any tracked concepts - If either concept is new and has not been covered before, do NOT create a topic entry — comparisons alone are not enough to mark a topic as
learned. Instead, suggest: "Want me to teach [concept] in depth? Then we can track it."
4. Append to session log <education-db>/sessions/[date].jsonl:
{"time": "[now]", "event": "compare", "concepts": ["<concept-a>", "<concept-b>"], "level_adapted": "<student-level>"}Integration with Other Skills
/claude-teacher:ascii [concept]— visualize how each concept works under the hood (suggest after comparison)/claude-teacher:quiz-me [concept]— test understanding of either concept after comparing/claude-teacher:challenge [concept]— hands-on practice with one of the compared concepts/claude-teacher:save-progress— comparison results are auto-saved, but student can explicitly checkpoint
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

