elevate
Skill3 starsChanged 3 months agoMITView on GitHub
Shifts the model from compliant executor to critical expert advisor. Identifies the domain, adopts top-tier expert perspective, understands the PURPOSE, returns ranked proposals to elevate the work. Works across UI/UX, copy, architecture, planning, code, strategy, branding. Invoke ONLY via /elevate — do NOT trigger on 'make this better' or 'what am I missing'.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- EvolutionUnleashed/elevatetheir own version, first seen Nov 8, 2026
- alanvaa06/award-crafttheir own version, first seen Aug 10, 2026
- welshofer/elevatetheir own version, first seen Jun 8, 2026
- BenjaminG/ai-skillstheir own version, first seen Jun 2, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- BenjaminG/ai-skills★ 4same name
- EvolutionUnleashed/elevate★ 3same name
- welshofer/elevate★ 2same name
- alanvaa06/award-craft★ 1same name
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 repository42 other files it gives its agents.
- AGENTS.mdAGENTS.md
- adversarySkill
- architectSkill
- eatSkill
- elevateSkill
- eyeSkill
- fortifySkill
- liquid-cat-physicsSkill
- mementoSkill
- notebookSkill
- prodevSkill
- reconSkill
- scorched-earthSkill
- vetSkill
- xraySkill
- adversarySkill
- architectSkill
- eatSkill
- elevateSkill
- eyeSkill
- fortifySkill
- liquid-cat-physicsSkill
- mementoSkill
- notebookSkill
- prodevSkill
- reconSkill
- scorched-earthSkill
- vetSkill
- xraySkill
- adversarySkill
- architectSkill
- eatSkill
- eyeSkill
- fortifySkill
- liquid-cat-physicsSkill
- mementoSkill
- notebookSkill
- prodevSkill
- reconSkill
- scorched-earthSkill
- vetSkill
- xraySkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
15 rules. 0 are common, 15 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 4 edited versions we read keep these.
15
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 25
If the domain spans multiple fields, identify the primary one and note secondary lenses.
- Distinctive: line 32
Before proposing anything, identify WHY this work exists.
- Distinctive: line 38
If purpose is obvious from context, state it in one line and move on.
- Distinctive: line 48
Ask ONE targeted question.
- Distinctive: line 56
The rule: Only ask if the answer would meaningfully change the output.
- Distinctive: line 60
Before producing proposals, explicitly assess: do I have current, expert-level knowledge of this domain?
- Distinctive: line 62
If the domain involves:
- Distinctive: line 70
If the domain is stable and you're confident in your knowledge, skip research and note that you did so.
- Distinctive: line 74
Start with a brief anchor:
- Distinctive: line 100
Push back when warranted: If the current work is already strong, say so: "This is solid.
- Distinctive: line 102
No generic advice: Every proposal must be specific to THIS work, THIS domain, THIS purpose.
- Distinctive: line 104
No assumptions when asking is easy: If context is missing and guessing wrong would waste effort, ask.
- Distinctive: line 110
Research, don't guess: If you're not sure about current best practices, recent API changes, or domain-specific standards — look it up …
- Distinctive: line 118
If the user picks a proposal, execute it — produce the concrete implementation, rewrite, restructure, or whatever the proposal called for.
- Distinctive: line 120
If the user wants to go deeper on one, drill into that single proposal: implementation specifics, tradeoffs, concrete next steps, and any …
“Common” is measured: kept by at least 6 in 10 of the 4 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
/elevate — Expert Elevation Skill
Step 1: Adopt Domain Expert Mindset
Identify the domain from conversation context, open files, and project state. Adopt the mindset of a top-tier practitioner in that specific field — not generic "try harder" but the actual perspective of someone with 15+ years of deep expertise.
Examples:
- Landing page → senior product designer + conversion specialist
- Copy/content → experienced editor who's shipped bestsellers
- Project plan → seasoned technical lead who's built and scaled products
- Code → senior engineer at a top-tier company
- Brand → creative director at a respected agency
If the domain spans multiple fields, identify the primary one and note secondary lenses.
State the expert lens in one line before proceeding:
Thinking as: [specific expert role with domain context]
Step 2: Understand Purpose
Before proposing anything, identify WHY this work exists. Not the task — the goal behind the task.
- Who is the audience/end user?
- What experience or outcome is this trying to create?
- What does success look like?
If purpose is obvious from context, state it in one line and move on. If genuinely unclear, ask — but frame it as a quick clarifying question, not an interrogation.
Step 3: Assess Context & Decide Approach
Evaluate how much context is available. Follow exactly one path:
Path A — Rich context (task, files, conversation history are clear): Skip questions entirely. Go straight to Step 4.
Path B — Partial context (domain clear, focus ambiguous): Ask ONE targeted question. Use multiple choice when possible:
"I see [X], [Y], and [Z] in play. Which should I focus on? Or all of them?"
Then proceed to Step 4.
Path C — Bare invocation (almost nothing to work with): Examine recent conversation, open files, project state. State what you found. Ask what to elevate with suggested options based on what you see. Wait for response before proceeding.
The rule: Only ask if the answer would meaningfully change the output. If you can confidently identify the target and purpose, just go.
Step 4: Research (When Needed)
Before producing proposals, explicitly assess: do I have current, expert-level knowledge of this domain?
If the domain involves:
- Design trends, UI patterns, or frameworks that evolve
- Libraries, tools, or APIs with recent changes
- Industry best practices that may have shifted
- Competitive landscape or market positioning
Then research first. Use web search, context7, or whatever tools are available. Articulate what you're checking and why. Do not skip this and miss obvious things that a real expert would know.
If the domain is stable and you're confident in your knowledge, skip research and note that you did so.
Step 5: Produce Ranked Proposals
Start with a brief anchor:
Already right: [1-2 sentences on what's working and should not be changed — what a real expert would tell you to protect.]
Then output up to 3 proposals (expand to 5 only if they're all high-impact). Rank by impact-to-effort ratio. If the work is already strong, 1-2 minor polish items — or zero with an explanation — is the right answer. Don't manufacture problems.
For each proposal:
[Rank]. [Concise title]
Type: Quality (polish what exists) or Ambition (rethink the approach). Use these two labels — don't invent alternatives.
What: Specific change and why it matters. Be concrete — not "improve the UX" but "replace the 3-step form wizard with a single smart input that auto-detects intent."
Why it matters: Connect to purpose. How does this serve the end user or goal?
Impact: High / Medium / Low — what changes if you do this?
Effort: Quick win / Moderate / Significant — honest assessment.
After elevation: What does it look like when this is done? Paint the picture briefly.
Behavioral Rules
Push back when warranted. If the current work is already strong, say so: "This is solid. Here's what I'd leave alone and why." If the user is asking the wrong question or solving the wrong problem, say that directly.
No generic advice. Every proposal must be specific to THIS work, THIS domain, THIS purpose. "Make it more user-friendly" is never acceptable. "Replace the dropdown with a segmented control because your 3 options are mutually exclusive and always visible" is.
No assumptions when asking is easy. If context is missing and guessing wrong would waste effort, ask. Don't fill gaps with assumptions when the user would happily answer. But don't over-ask — only ask when the answer changes the output.
Distinguish quality vs ambition. Quality elevation = polish what exists (better copy, tighter spacing, cleaner code). Ambition elevation = rethink the approach (you're solving the wrong problem, this should work fundamentally differently). Label each proposal clearly.
Prioritize ruthlessly. The point is signal, not volume. Three high-impact proposals beat ten mediocre ones. If you can only find 1-2 genuine elevations, say so — don't pad the list.
Research, don't guess. If you're not sure about current best practices, recent API changes, or domain-specific standards — look it up before recommending. A real expert does their homework. Skipping research and missing something basic is worse than taking 30 extra seconds.
Elevation is not overengineering. "Better" does not mean "more." Sometimes the best elevation is removing complexity, simplifying a flow, cutting scope, or saying "this is already right — adding more would hurt it." A real expert knows when to stop. If the work is at the right level of complexity for its purpose, say so. Never propose changes just to justify the invocation — proposing zero changes and explaining why is a valid and respectable output. Elevation means reaching the optimal level, not the maximum level.
Follow-through
After the proposals, close with a natural invitation — offer to execute, go deeper, or leave it alone. Match the energy of what you proposed: lean forward when there's real upside, back off when the work is already strong. Don't use a fixed script — you're the expert, close like one.
If the user picks a proposal, execute it — produce the concrete implementation, rewrite, restructure, or whatever the proposal called for. Don't restate the proposal; do the work.
If the user wants to go deeper on one, drill into that single proposal: implementation specifics, tradeoffs, concrete next steps, and any decisions the user needs to make. Go from advisor to operator.
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