Search the docs, videos, blog, apps, teams, skills and release notes.
At a glance
What it is
Complete guidance for science fair projects including project selection by age, interest, and available resources, scientific method walkthrough, hypothesis formation, experiment design, data collection and analysis, display board creation, presentation coaching, and understanding judging criteria.
A skill is a written procedure a bot loads when a job calls for it. This one is a single file, SKILL.md, and the whole file is on this page.
The whole file, exactly as it downloads. Read it before you rely on it.
SKILL.md
505 lines · 2,914 words
Gather requirements. Ask the user clarifying questions about their specific context, goals, constraints, and experience level.
Analyze the situation. Review the information provided and identify key factors, challenges, and opportunities relevant to science fair advisor.
Complete guidance for science fair projects including project selection by age, interest, and available resources, scientific method walkthrough, hypothesis formation, experiment design, data collection and analysis, display board creation, presentation coaching, and understanding judging criteria.
Nothing. It ships with Murage, which is open source. Your bots run on the AI plan you already have.
Yes. Open it in Settings → Skills to read, edit or duplicate it. Skill Guard scans it again after every edit.
Download the app, connect the AI you already pay for, and tell your Chief of Staff what needs doing. Plan on about ten minutes from install to a working team.
No account needed · Runs on the AI plan you already pay for
Paste it into your agent's instructions (CLAUDE.md, AGENTS.md or a custom GPT), or add it to a bot in Murage.
Ask Ember for the bot, then switch the skill on in its settings.
Step 1
Send your Chief of Staff this message. It proposes the bot and its role first, and creates it when you say go.
Send this to Ember
“Create a bot that uses the Science Fair Advisor skill, and show me the plan first.”
You're done when your Chief proposes the bot and its role, and the bot appears in your sidebar once you say go.
Step 2
You're done when you see the bot’s skills and the library.
Step 3
You're done when the skill shows as on for that bot.
Step 4
You're done when the bot takes the job and opens the skill when it needs it.
Prefer to do it yourself? Choose + in the sidebar, then New Bot.Read the full guide to skills and Skill Guard
What it teaches a bot, what it covers, and the whole file to read.
What it covers
When to Use
Process
Questions to Ask First
Phase 1: Project Selection
Phase 2: The Scientific Method
Phase 3: Data Collection and Analysis
Phase 4: Display Board Creation
Phase 5: Presentation Coaching
Phase 6: Judging Criteria
Project Timeline Template
Output Format
Example
Edge Cases
Develop the framework. Create a structured approach tailored to the user's needs, incorporating best practices and domain-specific considerations.
Deliver actionable output. Present specific, implementable recommendations with clear rationale, timelines, and success criteria.
Address edge cases. Proactively identify potential issues, alternative approaches, and contingency plans.
Use this skill when:
User needs guidance on science fair advisor
User asks about science fair advisor best practices or techniques
User wants a structured approach to science fair advisor
Do NOT use this skill when:
A more specialized skill exists for the specific subtopic
The request is outside the scope of science fair advisor
What grade level is the student?
What are the student's interests (animals, sports, food, technology, space, environment)?
What is the deadline for the project, and how much time is available?
Are there specific rules or requirements from the school or fair (categories, length, display size)?
What is the budget for materials?
Where will the experiment be conducted (home, school, outdoor)?
Does the project need to be an experiment, or are demonstrations and models acceptable?
Are there any restrictions on project types (no live vertebrate animals, no hazardous chemicals)?
Has the student done a science fair project before?
Is the student doing this independently, or is parent/mentor involvement expected?
Grades K-2 (Ages 5-8) -- Observational and Simple Comparison Projects:
Does the color of light affect plant growth?
Which paper towel brand is the strongest?
Do different surfaces affect how far a toy car rolls?
What material keeps ice from melting the longest?
Do all liquids freeze at the same temperature?
How does temperature affect how high a ball bounces?
Which type of soil holds the most water?
Grades 3-5 (Ages 8-11) -- Controlled Experiments:
Does music affect plant growth?
Which bridge design holds the most weight?
How does salt concentration affect water's boiling point?
Do different colors absorb heat differently?
Which natural substance cleans pennies best?
How does the angle of a ramp affect the speed of a rolling ball?
Does the type of water affect seed germination?
How does surface area affect evaporation rate?
Grades 6-8 (Ages 11-14) -- Multi-Variable Experiments:
How do different fertilizers affect plant growth over time?
Does the shape of a wing affect lift?
How does pH level affect enzyme activity?
What factors affect the strength of an electromagnet?
How does water quality affect brine shrimp survival?
Does music tempo affect heart rate during exercise?
How effective are different water filtration methods?
What factors affect solar panel efficiency?
Grades 9-12 (Ages 14-18) -- Advanced Research Projects:
How do microplastics affect seed germination and root growth?
Can machine learning predict local weather patterns better than traditional methods?
How does antibiotic concentration affect bacterial resistance development?
What is the relationship between urban heat islands and green space?
How do different wavelengths of light affect photosynthesis rates?
Can natural dyes produce viable solar cells?
How does social media usage correlate with sleep quality in teenagers?
PROJECT EVALUATION MATRIX
=========================
Rate each factor 1-5 (5 = best fit)
Factor | Project A | Project B | Project C
--------------------------------+-----------+-----------+----------
Student interest level | _______ | _______ | _______
Feasibility (time available) | _______ | _______ | _______
Materials accessible/affordable | _______ | _______ | _______
Testable with clear variables | _______ | _______ | _______
Safe to conduct | _______ | _______ | _______
Measurable results | _______ | _______ | _______
Age-appropriate complexity | _______ | _______ | _______
Originality/creativity | _______ | _______ | _______
--------------------------------+-----------+-----------+----------
TOTAL | _______ | _______ | _______Step 1: Ask a Question A good science fair question is:
Specific and focused (not too broad)
Testable through experimentation
Measurable (you can collect data)
Interesting to the student
Format: "How does [independent variable] affect [dependent variable]?"
Examples:
"How does the amount of sunlight affect the growth rate of bean plants?"
"How does the temperature of water affect how quickly sugar dissolves?"
Step 2: Research the Topic Before experimenting, learn what is already known:
Read books, articles, and reliable websites about the topic
Understand the science behind the question
Find out what similar experiments have shown
Identify variables and measurement methods used by others
Record sources for the bibliography
Step 3: Form a Hypothesis A hypothesis is an educated guess based on research.
Format: "If [I change the independent variable], then [the dependent variable will...] because [scientific reasoning]."
Example: "If I increase the amount of sunlight bean plants receive, then they will grow taller because photosynthesis increases with more light energy."
Key characteristics:
Must be testable
Must be specific and measurable
Based on research, not random guessing
Written before the experiment begins
It is okay to be wrong -- that is still good science
Step 4: Design the Experiment
Identify your variables:
Independent variable: What you change on purpose (only ONE)
Dependent variable: What you measure (the result)
Controlled variables: Everything you keep the same (to make it a fair test)
Example:
Question: How does sunlight affect bean plant growth?
Independent variable: Hours of sunlight per day (2, 4, 6, 8 hours)
Dependent variable: Plant height in centimeters
Controlled variables: Same type of bean, same pot size, same soil,
same amount of water, same starting date, same temperatureSample size and trials:
Run at least 3 trials (repetitions) for each condition
More trials = more reliable data
For living things, use multiple specimens per condition
Step 5: Conduct the Experiment
Follow your procedure exactly
Record all observations and measurements
Note anything unexpected
Take photos at regular intervals
Record data in an organized table or spreadsheet
Do NOT change your procedure midway (if you must, note it)
Step 6: Analyze Data
Calculate averages across trials
Create graphs and charts to visualize results
Look for patterns and trends
Calculate relevant statistics (mean, median, range)
Determine if results support or contradict your hypothesis
Step 7: Draw Conclusions
State whether results supported your hypothesis
Explain why you think you got these results
Discuss any errors or problems
Suggest improvements for future experiments
Propose follow-up questions
DATA COLLECTION TABLE
======================
Experiment: _________________________________
Date Range: _____________ to _____________
Condition | Trial 1 | Trial 2 | Trial 3 | Average
----------------+---------+---------+---------+--------
[Condition 1] | _______ | _______ | _______ | _______
[Condition 2] | _______ | _______ | _______ | _______
[Condition 3] | _______ | _______ | _______ | _______
[Condition 4] | _______ | _______ | _______ | _______
[Control] | _______ | _______ | _______ | _______
Units of measurement: _____________
Measurement tool: _____________
Measurement frequency: _____________| Data Type | Best Graph | When to Use |
|---|---|---|
| Comparing categories | Bar graph | Comparing different groups or conditions |
| Change over time | Line graph | Showing trends over days/weeks |
| Parts of a whole | Pie chart | Showing percentages or proportions |
| Relationship between two variables | Scatter plot | Showing correlation between variables |
| Distribution of data | Histogram | Showing frequency of measurements |
Title that describes what the graph shows
Labeled x-axis (independent variable) with units
Labeled y-axis (dependent variable) with units
Consistent scale on both axes
Data points clearly marked
Legend if multiple data sets
Clean and easy to read
+------------------+------------------+------------------+
| | | |
| BACKGROUND | TITLE | RESULTS |
| RESEARCH | | |
| | (centered, | Data Tables |
| What you | large font) | |
| learned before | | Graphs |
| experimenting | | |
| | | |
+ +------------------+ +
| | | |
| HYPOTHESIS | MATERIALS | CONCLUSION |
| | AND | |
| | PROCEDURE | Analysis |
| | | |
| QUESTION | Photos of | What you |
| | setup and | learned |
| | process | |
| | | Future |
| | | research |
+------------------+------------------+------------------+
LEFT CENTER RIGHT
(Background) (Methods) (Results)Visual Design:
Use a consistent color scheme (2-3 colors maximum)
Black or dark text on light backgrounds for readability
Section headers in larger, bold font
Body text minimum 16-point font (must be readable from 3 feet away)
Consistent alignment and spacing
Photos and charts should be high quality and clearly labeled
Borders or frames around sections for organization
Content Guidelines:
Keep text concise -- bullets and short paragraphs
Let visuals (graphs, photos) do heavy lifting
Every section should have a clear heading
Proofread everything multiple times
Have someone else read it for clarity
What NOT to Do:
Do not handwrite text (print or type everything)
Do not overcrowd the board
Do not use clip art or unrelated decorations
Do not make the title too small
Do not include unnecessary information
Do not use light-colored text on light backgrounds
Title: Clear, specific, and engaging. Include the question or a catchy version of it.
Question: State your research question clearly.
Hypothesis: State your prediction and reasoning.
Background Research: Summarize key findings from research (3-5 paragraphs). Cite sources.
Materials: Complete list of everything used.
Procedure: Numbered steps someone else could follow to replicate your experiment.
Results: Data tables and graphs with clear labels. State the results factually without interpretation.
Conclusion: Did results support or contradict the hypothesis? Why? What were sources of error? What would you do differently? What follow-up questions arose?
Bibliography: All sources in proper format (ask teacher which citation style).
Opening (30 seconds): "My name is _______ and my project is about _______. I wanted to find out _______."
Background (30-60 seconds): "Before I started my experiment, I researched _______. I learned that _______."
Hypothesis (15 seconds): "Based on my research, I predicted that _______."
Procedure (30-60 seconds): "To test my hypothesis, I _______. I measured _______ and controlled _______."
Results (60 seconds): "My results showed _______." [Point to graphs/data on board.] "As you can see in this graph, _______."
Conclusion (30 seconds): "My hypothesis was [supported/not supported]. I think this happened because _______."
What I Learned (15-30 seconds): "If I did this again, I would _______. A good follow-up experiment would be _______."
Why did you choose this topic?
What was the hardest part of this project?
What would you do differently if you did it again?
What surprised you about your results?
How do your results relate to real-world applications?
What was your sample size, and do you think it was enough?
What were your controlled variables, and why did you control them?
Did anything go wrong during your experiment?
What would be a good follow-up experiment?
How confident are you in your results?
Body Language:
Stand to the side of your board, not in front of it
Face the judges, not the board
Use a pointer or gesture to direct attention to specific areas
Make eye contact
Stand up straight with hands visible (not in pockets)
Voice:
Speak loudly enough to be heard clearly
Slow down (nervousness speeds up speech)
Show enthusiasm for your project
Practice with a timer at home
Attitude:
It is okay to say "I don't know, but I could find out by..."
It is okay if your hypothesis was wrong -- explain what you learned
Show genuine curiosity and interest in the science
Thank judges at the end
| Category | Weight | What Judges Look For |
|---|---|---|
| Scientific thought | 25-30% | Clear question, testable hypothesis, proper experimental design, controlled variables |
| Thoroughness | 20-25% | Adequate trials, complete data, careful execution, attention to detail |
| Skill and clarity | 15-20% | Appropriate methods, accurate measurements, clear presentation |
| Creativity/originality | 15-20% | Unique question, creative approach, novel application |
| Display and presentation | 10-15% | Organized board, clear communication, ability to answer questions |
Strong projects share these characteristics:
A specific, focused question that the student is genuinely curious about
Thorough background research that informs the experimental design
Well-designed experiment with clear variables and adequate controls
Multiple trials with consistent methodology
Accurate data collection with appropriate tools
Clear, honest analysis (including errors and unexpected results)
Thoughtful conclusions that connect back to the hypothesis and broader science
Professional, organized display board
Student can explain every aspect of the project confidently
Student shows genuine enthusiasm and understanding
SCIENCE FAIR PROJECT TIMELINE
===============================
Fair/Due Date: _______________
Start Date: _______________
Week 1-2: PLANNING
[ ] Choose topic and research question
[ ] Get teacher/parent approval
[ ] Begin background research
[ ] Form hypothesis
Week 2-3: DESIGN
[ ] Design experiment (variables, controls, procedure)
[ ] Create materials list
[ ] Gather materials
[ ] Create data collection sheets
Week 3-5: EXPERIMENT
[ ] Conduct experiment (multiple trials)
[ ] Record all data carefully
[ ] Take photos of setup and process
[ ] Note any problems or unexpected observations
Week 5-6: ANALYSIS
[ ] Organize data into tables
[ ] Create graphs and charts
[ ] Analyze results
[ ] Draw conclusions
Week 6-7: DISPLAY AND PRESENTATION
[ ] Create display board
[ ] Write all sections
[ ] Print photos and graphs
[ ] Assemble board
[ ] Practice presentation
[ ] Prepare for judge questions
Week 7: FINAL PREP
[ ] Final review of board for errors
[ ] Practice presentation with timer
[ ] Prepare any demonstration materials
[ ] Get a good night's sleep before the fairChoosing a topic that is a demonstration, not an experiment (volcanoes, unless you are testing a variable)
Starting too late and rushing the experiment
Only doing one trial (always do at least three)
Changing the procedure mid-experiment without noting it
Making up or adjusting data to match the hypothesis
Having a parent do most of the work (judges can tell)
skipping to document the process with photos
Not being able to explain the science behind the project
Choosing a project that is too complex for the time or resources available
Not practicing the oral presentation before the fair
The best science fair projects come from genuine curiosity. Help the student find a question they actually want to answer, and the motivation to do good work will follow naturally.
Deliver the response as a structured document with clear headings and actionable content. Use tables for comparisons, numbered lists for sequential steps, and bullet points for options. Include specific examples where applicable.
[Science Fair Advisor deliverable]
1. Context and objectives
2. Analysis or framework
3. Specific recommendations with rationale
4. Action items with timelineInput: "Help me with science fair advisor for a mid-size project."
Output: A complete science fair advisor framework tailored to the specific context, with actionable steps, relevant considerations, and measurable outcomes.
Incomplete information: Ask clarifying questions before proceeding rather than making assumptions
Conflicting requirements: Identify trade-offs explicitly and present options with pros and cons
Scale mismatch: Adapt recommendations to match the user's context (individual vs. team vs. organization)
Domain crossover: When the request overlaps with other skill domains, address what falls within scope and reference specialized skills for the rest
SKILL.md
505 lines · 2,914 words
The text of SKILL.md is shown as it downloads, under the Apache-2.0 license, by Ferrox Labs. The license is the one in the file's own frontmatter.
Your new bot
Science Fair Advisor bot
Waiting in your sidebar once you say go.
No account needed · Runs on the AI plan you already pay for