Proposal Review
Produce a rigorous, decision-ready review for AI/ML, computational biology, and bioscience proposals. Be fair, skeptical, specific, and explicit about missing information.
Instructions
- Read the proposal and identify the decision context if provided: sponsor goals, rubric, budget cap, timeline, and risk tolerance.
- If critical information is missing, do not invent it. Flag the gap and turn it into a prioritized question for the PI.
- Structure the review with these sections:
- Executive summary
- Heilmeier catechism
- Technical merit
- Data, compute, and experimental resources
- Risk register
- Team and execution capability
- Ethics, safety, and compliance
- Budget and schedule realism
- Scorecard
- Decision and funding conditions
- Questions for the PI
- Tailor the technical review to the proposal type:
- AI/ML: baselines, ablations, leakage prevention, calibration, external validation, compute realism
- Bio or wet lab: controls, replicates, statistical plan, assay feasibility, translational path
- Include at least six risks covering technical, data or experimental, budget or timeline, and adoption or regulatory concerns when relevant.
- Provide a weighted scorecard on a 1 to 5 scale with short justifications for each score.
- End with a clear funding recommendation:
Strong Accept, Accept, Borderline, or Reject.
- Keep the review concrete and action-oriented. Reference proposal details when available and name fatal flaws plainly.
Quick Reference
| Task |
Action |
| Summarize proposal |
Describe aims, novelty, and bottom-line recommendation in <=150 words |
| Test strategic logic |
Answer the Heilmeier catechism explicitly |
| Review feasibility |
Check assumptions, methods, milestones, and resource realism |
| Review rigor |
Assess controls, baselines, validation, statistics, and reproducibility |
| Review risk |
Build a risk register with likelihood, impact, warning signs, and mitigations |
| Make a decision |
Give a final recommendation plus concrete funding conditions or rejection reasons |
Input Requirements
- Proposal text or a linkable proposal excerpt
- Optional sponsor or program context
- Optional scoring rubric, budget cap, and timeline constraints
Output
- A decision-ready structured proposal review
- A weighted scorecard with justified subscores
- A clear funding recommendation and conditions
- A prioritized list of questions that could change the decision
Quality Gates
Examples
Example 1: Review a computational biology grant draft
Review this proposal for a microbiome foundation-model project. Use a 1-5 scorecard,
identify fatal flaws if any, and list conditions for funding.
Example 2: Review with sponsor constraints
Review this translational bioscience proposal for a program with a 24-month timeline,
$1.5M budget cap, and high concern for regulatory risk.
Troubleshooting
Issue: The proposal is missing a clear evaluation plan
Solution: Mark this as a major weakness, explain what convincing evidence would look like, and add PI questions about milestones and success metrics.
Issue: The budget or timeline is hard to judge
Solution: State the uncertainty, identify the likely critical path, and evaluate whether the claimed scope is credible under the stated constraints.
Issue: Ethics or compliance details are absent
Solution: Treat the omission as a potential blocker and ask targeted questions about subjects, privacy, biosafety, or regulatory readiness.
Related Skills
/manuscript-review-council — equivalent pipeline for manuscripts/scientific-writing — draft or revise the proposal narrative/bio-logic — assess methodology and evidence rigor
1---2name: proposal-review3description: Structured, decision-ready review framework for AI/ML, computational biology, and bioscience proposals. Use when evaluating grant, project, or funding proposals.4---5
6# Proposal Review
7
8Produce a rigorous, decision-ready review for AI/ML, computational biology, and bioscience proposals. Be fair, skeptical, specific, and explicit about missing information.
9
10## Instructions
11
121. Read the proposal and identify the decision context if provided: sponsor goals, rubric, budget cap, timeline, and risk tolerance.
132. If critical information is missing, do not invent it. Flag the gap and turn it into a prioritized question for the PI.
143. Structure the review with these sections:
15 - Executive summary
16 - Heilmeier catechism
17 - Technical merit
18 - Data, compute, and experimental resources
19 - Risk register
20 - Team and execution capability
21 - Ethics, safety, and compliance
22 - Budget and schedule realism
23 - Scorecard
24 - Decision and funding conditions
25 - Questions for the PI
264. Tailor the technical review to the proposal type:
27 - AI/ML: baselines, ablations, leakage prevention, calibration, external validation, compute realism
28 - Bio or wet lab: controls, replicates, statistical plan, assay feasibility, translational path
295. Include at least six risks covering technical, data or experimental, budget or timeline, and adoption or regulatory concerns when relevant.
306. Provide a weighted scorecard on a 1 to 5 scale with short justifications for each score.
317. End with a clear funding recommendation: `Strong Accept`, `Accept`, `Borderline`, or `Reject`.
328. Keep the review concrete and action-oriented. Reference proposal details when available and name fatal flaws plainly.
33
34## Quick Reference
35
36| Task | Action |
37|------|--------|
38| Summarize proposal | Describe aims, novelty, and bottom-line recommendation in <=150 words |
39| Test strategic logic | Answer the Heilmeier catechism explicitly |
40| Review feasibility | Check assumptions, methods, milestones, and resource realism |
41| Review rigor | Assess controls, baselines, validation, statistics, and reproducibility |
42| Review risk | Build a risk register with likelihood, impact, warning signs, and mitigations |
43| Make a decision | Give a final recommendation plus concrete funding conditions or rejection reasons |
44
45## Input Requirements
46
47- Proposal text or a linkable proposal excerpt
48- Optional sponsor or program context
49- Optional scoring rubric, budget cap, and timeline constraints
50
51## Output
52
53- A decision-ready structured proposal review
54- A weighted scorecard with justified subscores
55- A clear funding recommendation and conditions
56- A prioritized list of questions that could change the decision
57
58## Quality Gates
59
60- [ ] Missing information is flagged instead of invented
61- [ ] The review covers novelty, rigor, feasibility, risks, team, ethics, and budget
62- [ ] At least six concrete risks are documented with mitigations
63- [ ] The final recommendation is explicit and consistent with the evidence
64
65## Examples
66
67### Example 1: Review a computational biology grant draft
68
69```text
70Review this proposal for a microbiome foundation-model project. Use a 1-5 scorecard,
71identify fatal flaws if any, and list conditions for funding.
72```
73
74### Example 2: Review with sponsor constraints
75
76```text
77Review this translational bioscience proposal for a program with a 24-month timeline,
78$1.5M budget cap, and high concern for regulatory risk.
79```
80
81## Troubleshooting
82
83**Issue**: The proposal is missing a clear evaluation plan
84**Solution**: Mark this as a major weakness, explain what convincing evidence would look like, and add PI questions about milestones and success metrics.
85
86**Issue**: The budget or timeline is hard to judge
87**Solution**: State the uncertainty, identify the likely critical path, and evaluate whether the claimed scope is credible under the stated constraints.
88
89**Issue**: Ethics or compliance details are absent
90**Solution**: Treat the omission as a potential blocker and ask targeted questions about subjects, privacy, biosafety, or regulatory readiness.
91
92## Related Skills
93
94- `/manuscript-review-council` — equivalent pipeline for manuscripts
95- `/scientific-writing` — draft or revise the proposal narrative
96- `/bio-logic` — assess methodology and evidence rigor
gabrielmoreira