agentsclimarketplace

Grill me

Skill scoobydont-666/shared-claude-skills/skills/grill-me

10 production-tested Claude Code skills — model routing, security hardening, code quality, tax advisory, cost optimization. Install: clone to ~/.claude/skills/

Install
npx -y skills add scoobydont-666/shared-claude-skills --skill grill-me

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Structured interrogation methodology for stress-testing plans, designs, and decisions. Resolves decision tree branches through systematic questioning across 8 categories (requirements, constraints, edge cases, failure modes, scalability, security, tradeoffs, integration, maintenance). Invoked by write-a-prd and prd-to-plan during design validation.

SKILL.md

12.3 KB, as published. Nobody here has run it

Grill-Me: Comprehensive Design Interrogation

Purpose

Interview the user relentlessly about a plan or design until reaching shared understanding. Walk down each branch of the decision tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.

If a question can be answered by exploring the codebase, explore the codebase instead.


Question Categories

1. Requirements

What exactly are we building? For whom? What's explicitly out of scope?

  • User stories: Who is the primary user? What's their workflow end-to-end?
  • Success criteria: How do we know this is done? (metrics, KPIs, acceptance criteria)
  • Scope boundaries: What are we NOT building? What gets deferred?
  • Data model: What entities, relationships, and state transitions are involved?
  • Inputs/outputs: What data flows in? What's the output format? How is it consumed?
  • Completeness: Does this handle all user segments, or is it MVP-only?

2. Constraints

Time, resources, dependencies, technical limitations, and environmental factors.

  • Timeline: How long do we have? Are there hard deadlines? Milestones?
  • Team: Who builds this? What's their capacity? Skill gaps?
  • Tech stack: Can we use X? Are we locked into Y? Compatibility requirements?
  • Infrastructure: What do we have available? (GPUs, databases, storage, networking)
  • Dependencies: What existing systems must this integrate with? Are they blocking?
  • Budget: Cost constraints? Infrastructure costs? Third-party services?

3. Edge Cases

What happens when X fails? What about null/empty/concurrent states?

  • Empty states: What if the user has no data? No history? No context?
  • Boundary conditions: What's the smallest/largest valid input? What breaks at scale?
  • Concurrent operations: What if two users try to do this simultaneously? Race conditions?
  • Partial failures: What if the database is slow? Network is down? Service is degraded?
  • Invalid input: What happens if the user passes malformed data? Nulls? Extreme values?
  • State transitions: Are all state transitions valid? What's impossible and why?

4. Failure Modes

What breaks first? What's the blast radius? What's the rollback plan?

  • Dependency failures: If X service goes down, what happens to this system?
  • Data corruption: What if a database record is corrupted? How do we recover?
  • Performance degradation: What's the first thing that breaks under load?
  • Blast radius: If this fails, what else goes down with it? How many users are affected?
  • Recovery procedures: How long to recover? Who gets paged? What's the runbook?
  • Monitoring: How do we know it's broken before users complain?
  • Rollback: Can we instantly revert? Do we need data migration rollback?

5. Scalability

Does this work at 10x? 100x? Where does it break first?

  • Data volume: At what record count does performance degrade?
  • Throughput: How many concurrent requests can we handle? What's the bottleneck?
  • Query complexity: Which queries get slow? At what row count?
  • Storage: How much disk/memory do we need? Growth trajectory?
  • Network: Bandwidth constraints? Latency SLOs?
  • Failure scenarios at scale: Does the system degrade gracefully or cascade-fail?
  • Cost growth: Does cost grow linearly with load? Exponentially?

6. Security

Auth model? Trust boundaries? Data sensitivity? Who can do what?

  • Authentication: How do we know who the user is? Is single-factor enough?
  • Authorization: What can each role do? Are there privilege escalation risks?
  • Data sensitivity: What data needs encryption? At rest? In transit?
  • Trust boundaries: What systems/actors do we trust? Where are the boundaries?
  • Access control: Who can read/write/delete? Are there audit trails?
  • Injection risks: SQL injection? Code injection? Template injection?
  • Secrets management: Where do API keys live? How are they rotated?
  • Compliance: HIPAA? GDPR? SOC2? PCI-DSS? Do we care?

7. Trade-offs

What are we giving up? Is there a simpler approach? What's the cost of this choice?

  • Complexity vs. feature completeness: Can we ship a simpler v1?
  • Performance vs. maintainability: Is this premature optimization?
  • Consistency vs. availability: Are we willing to accept eventual consistency?
  • Cost vs. durability: Can we use cheaper storage if we accept higher failure rate?
  • Time to market vs. tech debt: Are we taking on debt? Is it worth it?
  • Alternatives: Did we consider approach B? Why is this better/worse?

8. Integration

How does this interact with existing systems? What breaks?

  • Upstream systems: What feeds data into this? What's the contract?
  • Downstream systems: What depends on this? What's the API contract?
  • Data consistency: Does this data need to sync with other systems? Eventually or immediately?
  • Breaking changes: Would deploying this break existing users/systems?
  • API versioning: If we change the API, how do clients upgrade?
  • Monitoring/observability: Can existing monitoring systems see this? Logs/traces/metrics?

9. Maintenance

Who maintains this? How does it get updated? How do you know it's broken?

  • Owner: Who is on-call? Who can debug? Who owns the runbook?
  • Runbooks: What's the troubleshooting flowchart? Is it documented?
  • Deployment: How do we safely deploy changes? Blue/green? Canary? Full rollout?
  • Testing: What tests validate this before production? Unit/integration/e2e?
  • Observability: What logs/metrics/traces prove it's working?
  • SLO/SLA: What's our uptime commitment? Response time SLA?
  • Alerting: What should trigger pages? What's signal vs. noise?
  • Lifecycle: How long will we maintain this? When do we sunset it?

Decision Tree Resolution Protocol

For Each Category:

  1. Ask the first question in the category
  2. Expect an answer — if the user says "I don't know" or "it depends", ask "on what?" or "how will you find out?"
  3. Pursue each branch until one of:
    • Resolved — concrete, actionable answer (not hand-waving)
    • Deferred — explicitly deferred with reason, owner, and target date
    • ⚠️ Blocker — identified as needing external input (e.g., customer decision, legal review)
  4. Track resolution status — maintain a running list of resolved/deferred/blocked items
  5. Only move to next category when current category branches are resolved or explicitly deferred
  6. No "I'll figure that out later" without a concrete plan for when/how/who

Example Resolution Statuses:

  • ✓ Requirements.user_stories — resolved: primary user is ops team, daily workflow is monitor → troubleshoot → update config
  • ⏸ Constraints.budget — deferred to finance review, owner: Alex, target: 2026-04-10
  • ⚠️ Failure_modes.recovery_time — blocker: depends on SLA decision (not yet made)

Depth Calibration

Quick Grill (5 min)

  • Requirements only (what are we building?)
  • Top 3 risks identified
  • Surface-level, no deep branching
  • Use for small changes or obvious decisions

Standard Grill (15 min)

  • All 9 categories, one question each
  • Surface-level exploration
  • Flag obvious gaps but don't deep-dive
  • Typical for feature work, small integrations

Deep Grill (30+ min)

  • All 9 categories, follow every thread
  • Resolve all branches to concrete answers or explicit deferral
  • Comprehensive risk and tradeoff inventory
  • Use for: architecture decisions, large features, cross-system changes, high-stakes designs

Ask the user at the start: "Quick grill (5 min), standard (15 min), or deep grill (30+ min)?"


Stop Criteria

Grill is complete when all of the following are true:

  1. ✓ All category branches are resolved or explicitly deferred (with reason, owner, date)
  2. ✓ No "I'll figure that out later" without a plan
  3. ✓ The user can explain the design back coherently (ask them to summarize)
  4. ✓ Remaining open questions have identified owners and target dates
  5. ✓ Top 3 risks are identified and mitigated (or risk is accepted consciously)
  6. ✓ Key tradeoffs are explicit (not buried or denied)

If you sense the user is evading a category or question, push back: "You're not answering the question directly. Why not?"


Output Format: Grill Summary

At the end, produce a structured summary document with these sections:

## Grill Summary — [Project Name]
Date: [today's date]

### Decisions Made
- [Category]: [Decision] (reasoning)
- [Category]: [Decision] (reasoning)

### Deferred Items
- [Category]: [Item] — deferred to [date], owner: [name], reason: [why]
- [Category]: [Item] — deferred to [date], owner: [name], reason: [why]

### Blockers
- [Category]: [Item] — needs [external decision/input], owner: [name]

### Risks Accepted
- [Risk]: [Mitigation or acceptance reason]
- [Risk]: [Mitigation or acceptance reason]

### Open Questions with Owners
- [Question] — owner: [name], target: [date]
- [Question] — owner: [name], target: [date]

### Confidence Level
[High / Medium / Low] — because [reason]

### Next Steps
1. [Action] — owner [name], due [date]
2. [Action] — owner [name], due [date]

Save this summary to the project repo or share with stakeholders.


Integration with Other Skills

write-a-prd invokes grill-me

During PRD creation, after gathering initial requirements:

  • Run standard grill on the proposed feature/service
  • Feed grill summary into the PRD as "Design Decisions" and "Open Questions"
  • Mark any deferred items as "Future Work"

prd-to-plan invokes grill-me

Before transforming a PRD into an implementation plan:

  • Run deep grill to validate the plan is technically feasible
  • Identify blockers before assigning work
  • Save grill output as reference for implementation phases

Anti-Patterns: What NOT to Do

Don't Accept Hand-Waving

  • User: "It depends on the load"

  • You: "On what? Give me a number. At what load does it break?"

  • User: "We'll figure out auth later"

  • You: "How? When? Who? If you don't know, that's a blocker."

  • User: "It's secure by default"

  • You: "Prove it. What's the threat model? What attack does this stop?"

Don't Accept Subject Changes to Avoid Hard Questions

  • User: "Let's not worry about failure modes, just ship it"

  • You: "What's the blast radius if this fails? Who gets paged? What's the runbook?"

  • User: "The ops team will figure out scaling"

  • You: "When? At what scale? What's the plan? Who owns this?"

Don't Grill on Cosmetic Decisions

  • Avoid: naming conventions, formatting, minor UI polish
  • Focus on: structural decisions that constrain future work

Don't Let "MVP" Be an Excuse for Lazy Thinking

  • User: "It's just an MVP, we don't need to worry about scalability"
  • You: "What does v2 look like? Will this architecture support it? If not, what technical debt are you taking on?"

How to Conduct the Grill

  1. Start with context: "Tell me about the plan. What are we building?"
  2. Ask the first question from the appropriate category
  3. Listen fully — don't interrupt
  4. Push on vagueness: "That's not concrete enough. Give me an example."
  5. Recommend an answer if you have one: "I'd suggest X because Y. Does that work?"
  6. Track resolutions in your grill summary
  7. When stuck: ask "What would unblock this?" or "Who owns this decision?"
  8. At the end: read back the summary and ask "Did I miss anything? Do you disagree with any of these decisions?"

Success Metrics

A grill is successful if:

  • The user leaves with fewer than 5 open questions (or all deferred with clear owners/dates)
  • The user can explain the design back to you without hesitation
  • You've identified top 3 risks and they're either mitigated or consciously accepted
  • All dependencies and blockers are surfaced
  • The team can execute the plan without discovering major design gaps mid-sprint

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.