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03 Optimization Function · Scientific Problem Selection · anthropics/knowledge-work-plugins · Skills Docs
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This skill helps scientists articulate HOW their project should be evaluated and define what success means. While Skill 2 focused on likelihood of success (the X-axis), this skill focuses on impact if successful (the Y-axis). The key insight: value is in the eye of a belief system —the value creation framework must be explicitly stated and led with.
“Pick the right optimization function.”
Different types of projects should be evaluated by different metrics. A common source of conflict between trainees and PIs, or authors and referees, is a misunderstanding about which category a project falls under. The root cause is often failure to articulate evaluation criteria clearly.
Every new discovery is irrelevance
Every new technology is non-use
Every company is death
Scientists must actively work against these defaults by choosing the right metrics and scoring well on at least one axis.
First, Claude should determine what type of project the user is pursuing:
Question 1: What is the primary goal?
A. Understand how biology works (fundamental knowledge)
B. Enable new experiments or capabilities (tool/technology)
C. Solve a practical problem (invention/application)
D. Something else (please describe)
Question 2: What would “success” look like in 3-5 years?
1-2 sentences describing the ideal outcome
Question 3: Who cares if this succeeds?
Academic researchers in the subfield?
Broader scientific community across fields?
Clinicians or practitioners?
Industry partners or companies?
General public or specific communities?
All of the above?
Based on the answers, Claude should help identify the right optimization function.
Axes: How much did we learn? × How general/fundamental is the object of study?
Philosophy: A high score on EITHER axis yields substantial impact. You don’t need both.
High Generality, Medium Learning: Ribosome stalling complex
Updates understanding of translation (fundamental process)
Scores well because translation is universal
Medium Generality, High Learning: Oxytricha germ-line nucleus
Genomic acrobatics may not be common to other organisms
BUT elegant mapping scores highly on how much we learned
May yield tools for genome editing (bonus)
High on Both Axes (Landmark): RNA interference, biomolecular condensates
These are rare—don’t expect every project to be here
But aim to score well on at least one axis
How many systems/organisms does this apply to?
Does it update understanding of a fundamental process?
Will textbooks need to be rewritten?
What new questions does this open?
Axes: How widely will it be used? × How critical is it for the application?
Philosophy: Again, high score on EITHER axis is sufficient.
Widely Used, Not Critical: BLAST
Used in countless projects
Rarely THE critical tool, but enormous cumulative impact
Not Widely Used, Highly Critical: Cryo-electron tomography
Too complicated for broad adoption
But generates stunning data that’s impossible to get otherwise
When you need it, nothing else works
High on Both Axes (Game-Changing):
GFP, CRISPR, AlphaFold (the famous ones)
But also: lentiviral delivery, cell sorting, massively parallel sequencing
Technologies we cannot imagine living without
How many labs would adopt this?
For what fraction of experiments is this THE enabling technology?
What becomes possible that wasn’t before?
How hard is it to implement?
Critical Rule: A tool that won’t be widely used AND isn’t critical for an application probably isn’t worth building.
Axes: How much good? × For how many people?
Philosophy: Useful for translational work, frugal science, global health.
Foldscope: Paper microscope accessible to millions of students globally
Neglected tropical disease intervention: Quality-adjusted life years per $100
Medical device: Number of patients who can access treatment
What problem does this solve?
How many people have this problem?
How much better is their life if you solve it?
What’s the cost per person helped?
Based on your Phase 1 responses, let me help you choose:
If you selected A (fundamental knowledge): → Basic Science Framework
If you selected B (enable experiments): → Technology Development Framework
If you selected C (solve practical problem): → Invention Framework
State Your Framework: “This project should be evaluated as [basic science/technology development/invention].”
Define Your Axes:
X-axis measures: [specific metric]
Y-axis measures: [specific metric]
Make Your Case:
X-axis score (Low/Medium/High): [Your assessment + reasoning]
Y-axis score (Low/Medium/High): [Your assessment + reasoning]
Threshold Check:
Do you score at least MEDIUM-HIGH on one axis?
If both are LOW-MEDIUM, you have a problem
Sometimes standard frameworks don’t fit. Examples where custom metrics work:
Alternative Metric Examples:
Frugal Science: How many children in low/middle-income countries gain access to microscopy?
Neglected Disease: Quality-adjusted life years saved per $100 invested
Sustainability: Tons of CO₂ equivalent prevented × cost-effectiveness
Equity: Reduction in disparity metric × number of people affected
When to propose alternative metrics:
Your work addresses a specific underserved need
Standard metrics miss your core value proposition
You’re working in an emerging area without established norms
Your work crosses traditional boundaries
How to propose alternative metrics:
Explain why standard metrics are insufficient
Define your proposed metric clearly
Provide a value creation index (two axes)
Show how your project scores on these axes
Even if absolute impact is hard to estimate, comparative assessment is valuable:
Exercise: Compare 3 Related Projects
For your project and two alternatives (either from literature or hypothetical):
Which would be most impactful if they all work?
Which has the best risk-adjusted impact?
Are you pursuing the best option?
If not, why? (Sometimes there are good reasons: resources, expertise, timing)
Scenario: You’re doing fundamental biology, but reviewers ask “How widely will this be used?”
Problem: They’re evaluating basic science with technology metrics
Solution: Explicitly frame as basic science. Lead with: “This updates our understanding of [fundamental process], which is conserved across [many systems].”
Scenario: You’re building a tool, but reviewers ask “How much did we learn about biology?”
Problem: They’re evaluating technology with basic science metrics
Solution: Explicitly frame as technology development. Lead with: “This enables experiments that are currently impossible, which [X] labs need for [Y] applications.”
Scenario: Your basic science is specific but deep, but reviewers want broad generality
Problem: They think both axes are required, rather than either/or
Solution: Explicitly acknowledge: “While this may not be universal, the depth of mechanistic insight scores highly on the learning axis.”
Scenario: You’re working on long-term fundamental research, but reviewers want immediate impact
Problem: Different value systems about when impact should materialize
Solution: Articulate your time horizon explicitly and provide historical examples of similar timelines
This is where Claude explicitly discusses the user’s belief system about what matters:
Questions for Reflection:
What drives the user?
Discovery and understanding?
Enabling others?
Solving problems?
Building things?
What would make the user proud?
Paper in Cell/Nature/Science?
Tool used by hundreds of labs?
Treatment reaching patients?
Opening a new field?
How does the user want to be remembered?
“Discovered X”
“Built Y that enabled Z”
“Solved problem W”
“Trained students who went on to…”
Whose approval matters?
Specific senior scientists in the field?
Broader community across fields?
Practitioners who use tools?
People whose lives are improved?
There are no wrong answers—but alignment matters:
The project should match the user’s value system
The evaluation framework should match the project type
Communication should lead with the framework
Claude should use PubMed to benchmark impact in the user’s area:
Impact Exemplars: Papers the user considers high-impact in the field
What framework did they use (implicitly or explicitly)?
How did they score on the axes?
What made them successful?
Analogous Projects: Similar approaches or systems
How were they evaluated?
What impact did they achieve?
What can be learned from their framing?
Field Expectations: What’s typical for the area?
Are basic science papers common?
Is technology development valued?
What level of impact is “good enough”?
Questions to ask the user:
What papers should be analyzed as benchmarks?
What search terms capture the field’s impact exemplars?
Are there specific journals or authors whose framing to emulate?
Once the framework is selected, here’s how to lead with it:
Opening Frame (within first 2 slides):
“The goal of this work is to understand [fundamental process X] in [general system Y]” → Basic science
“We’re developing a technology that will enable [critical experiment X] for [community Y]” → Technology
“This invention addresses [problem X] affecting [N] people” → Application
State your framework implicitly through word choice
Basic science: “reveals,” “demonstrates,” “shows that”
Technology: “enables,” “provides,” “makes it possible to”
Application: “solves,” “addresses,” “improves”
Explicitly name your evaluation framework
Provide the two-axis assessment
Score yourself on each axis with evidence
“I want to make sure we’re aligned on how this should be evaluated”
“I see this as [framework], scoring [X] on [axis 1] and [Y] on [axis 2]”
“Do you agree, or do you see it differently?”
“This matters because…” [explain downstream implications]
Claude should produce a 2-page Impact Assessment Document :
Type: Basic Science / Technology Development / Invention / Custom
Rationale: [Why this categorization fits]
X-Axis: [Metric name and definition]
Y-Axis: [Metric name and definition]
Custom Rationale (if applicable): [Why standard metrics don’t fit]
X-Axis Score: [Low/Medium/High]
Evidence: [Specific reasons for this score]
Examples: [Comparable projects or benchmarks]
PubMed Support: [Key papers that inform assessment]
Y-Axis Score: [Low/Medium/High]
Evidence: [Specific reasons for this score]
Examples: [Comparable projects or benchmarks]
PubMed Support: [Key papers that inform assessment]
Score on at least one axis: ☑ Yes / ☐ No
Strong justification: ☑ Yes / ☐ No
Aligned with your values: ☑ Yes / ☐ No
What Drives You: [Discovery/Enabling/Problem-solving/Building]
Success Definition: [What would make this worthwhile]
Approval Sources: [Whose opinion matters and why]
Framework Fit: [How project aligns with values]
[Specific mismatch type]
Scenario: [When this might happen]
Prevention: [How to frame to avoid it]
[Another mismatch]
Scenario: [When this might happen]
Prevention: [How to frame to avoid it]
Opening frame: [Exact language to use in first 2 slides]
Key phrases: [Vocabulary that signals your framework]
Abstract structure: [Framework-appropriate language]
Impact statement: [How to articulate in discussion]
Broader impact: [How to score yourself explicitly]
Justification: [Evidence for scores]
Alignment question: [Exact question to ask]
Your perspective: [How you see it]
Discussion points: [What matters for alignment]
[Specific step to strengthen X-axis score or argument]
[Specific step to strengthen Y-axis score or argument]
[Communication alignment with key stakeholders]
Framework: Basic science
X-Axis (Generality): HIGH—translation is universal
Y-Axis (Learning): MEDIUM—mechanism of one quality control system
Assessment: High on generality alone = substantial impact
Communication: “Updates our understanding of translation quality control”
Framework: Technology development
X-Axis (Widely Used): VERY HIGH—used by virtually all molecular biologists
Y-Axis (Critical): LOW-MEDIUM—helpful but rarely essential
Assessment: Extreme breadth of use = enormous cumulative impact
Communication: “Enables rapid sequence comparison across all biological databases”
Framework: Technology development
X-Axis (Widely Used): LOW—complex, expensive, specialized
Y-Axis (Critical): VERY HIGH—generates impossible-to-get-otherwise data
Assessment: Extreme criticality for niche = high impact
Communication: “Enables 3D visualization of molecular machines in native cellular context”
Framework: Invention (custom metric)
X-Axis (Good): MEDIUM—functional microscopy
Y-Axis (People): VERY HIGH—millions of students globally
Assessment: Massive reach × modest utility = transformative for education
Communication: “Democratizes microscopy for global education”
Value Is in the Eye of a Belief System: Make yours explicit.
Lead with Your Metric: Don’t assume others share your framework.
Either Axis Suffices: You don’t need both—just score well on one.
Articulate Early: Discuss with mentors before you’re 2 years in.
Avoid Default State: Work actively against irrelevance/non-use.
Compare, Don’t Absolute: Even rough comparison beats ignoring impact.
Align Communication: Your words should signal your framework.
Match Project to Values: Life is too short for misaligned work.
Inability to articulate which framework applies
Scoring LOW on both axes
Project type and evaluation framework don’t match
User and PI have different frameworks but haven’t discussed it
Using basic science metrics for a tool or vice versa
Never explicitly discussing impact assessment
Clear statement of optimization function
MEDIUM-HIGH score on at least one axis
Framework matches project type
Alignment with key stakeholders
Communication signals framework clearly
Benchmarking against comparable work
Claude should begin Phase 1 by asking:
What is the primary goal? (A/B/C/D)
What would success look like in 3-5 years?
Who cares if this succeeds?
Together, Claude and the user will select the right optimization function and position the work for maximum impact.
Remember: Impact assessment isn’t about ego—it’s about ensuring work matters in the way the scientist wants it to matter. Explicit framing prevents years of misalignment.
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