She Leads AISheLeadsAI.ai

The Ikigai Opportunity Lens Skill

Made by Anne Murphy with the Matriarchal Agentic Leadership Team

Ikigai Client Engagement Lens — Use Guide

A short companion to the skill. This lens answers one question — is this client right for you to take on? What it's for, when to reach for it, what the scores mean, and one full worked example.

What it does

You bring a prospective client engagement. It walks you through a 3-step read — Ikigai scoring, a commercial pressure-test, and a single most-important question to ask the client — then hands back a clear take-it-or-not recommendation and a branded Google Doc you can keep or share. It makes the call. No "it depends."

This is a fit decision about a client engagement. It is not a personal-purpose Ikigai exercise and not a general business-idea evaluator. The thing on the table is always a specific client and a specific engagement.

When to reach for it

Say any of these and it fires

Reach for it when a client engagement is on the table and the answer isn't obvious and you can feel yourself about to overthink it — referrals you feel obligated to take, shiny inbound that flatters you, anything where your gut and your calendar disagree.

What it already knows about you

Your practice profile is baked in. It won't ask what you offer, what energizes you, or your non-negotiables — it scores every prospect against those automatically. The one thing it asks each time is your current capacity, because that moves week to week. If your practice shifts, edit the profile block at the top of SKILL.md. That's the only place it lives.

What each Ikigai score means

You score four quadrants 1–5. Score it straight — the read is only as good as the inputs.

What you love — 1 is draining, 5 is energizing. The test is "would I do this even if no one was watching." A 5 fuels you. A 2 means six weeks in you'll resent your own calendar.

What you're great at — 1 is out of your depth, 5 is squarely in your zone. The test is built expertise, not "I could figure it out." Anything you'd be learning on their dime scores low.

What the world needs — 1 is nice-to-have, 5 is critical priority. The test is their urgency, not intellectual interest. A problem they'd pay to solve this quarter is a 5. A "someday" is a 2.

What you can be paid for — 1 is no signal, 5 is fully confirmed. The test is confirmed commercial signals — budget confirmed, timeline clear, decision-maker engaged. Vague enthusiasm with no budget is a 2, no however warm the call felt.

How it decides

Average scorePlusRecommendation
4.0 or higherbudget not a red flag, no non-negotiable hitSAY YES
3.0 or higherno non-negotiable hitSAY YES, BUT CLARIFY FIRST
Under 3.0— or any non-negotiable hitNOT YET

A non-negotiable hit drops it to NOT YET even at the highest score. That's the guardrail.

The One Question is the point

Every read ends with one question — the single most important thing to ask the prospect before you decide. It's chosen by what's weakest in the read. If the money is soft, the question is about budget and authority. If the energy is low, the question is about what you'd dread on a Monday. Ask it. The answer usually settles the call faster than another week of deliberating.

Worked example

You bring: "Inbound from a regional arts nonprofit. Came through a board member who heard me speak. They say they want help 'thinking about AI and fundraising.' Type feels like advisory, maybe a workshop. I'm at Partial capacity."

You score

Average — 3.5. No non-negotiable hit.

The read it returns

### Regional Arts Nonprofit — Ikigai Opportunity Read
Recommendation — SAY YES, BUT CLARIFY FIRST
The work is squarely in your zone and energizing, but the commercial side isn't grounded yet.
Ikigai alignment — 3.5/5
| Quadrant | Score | Read |
|—|—|—|
| What you love | 4/5 | Strong fit |
| What you're great at | 5/5 | Strong fit |
| What the world needs | 3/5 | Partial fit |
| What you can be paid for | 2/5 | Gap |
Friction
– Budget signal is soft — commercial commitment isn't confirmed.
– Buying authority hasn't been confirmed — you may be talking to a champion, not the check-signer.
—————————————————————————
THE ONE QUESTION
What budget has already been approved for solving this, and who specifically has the authority to release it?

You also get this as a styled SLAI Google Doc with the direct link, so you can drop it in a deal file or forward it.

What it won't do

It won't soften a gap to make you feel better, it won't hedge the call, and it won't decide for you. It's a blunt second opinion that respects your time — the yes or no is still yours.

Make it yours. Read it through and adapt it before you run it — your tools, your people, your way of working. It is built to be changed.
View the The Ikigai Opportunity Lens SKILL.md the file this guide runs on
---
name: ikigai-opportunity-lens
version: 1.0.0
description: >
  Use when Anne is deciding whether to take on a client engagement and says "should I take
  this client," "is this client right for me," "I have a prospect/lead," "run me through the
  Ikigai lens," "help me assess this engagement," "engagement check," "does this client fit my
  practice," or "I'm not sure if I should say yes to this." Scores a prospective client
  engagement through the Ikigai lens and returns a clear take-it-or-not recommendation, friction
  read, and The One Question — as a chat read plus a branded SLAI Google Doc.
---
# Ikigai Client Engagement Lens v1
## Banned Words Gate — Hardwired
Before drafting or presenting any output, read the live banned list fresh. Never rely on a remembered version of it, and never state a count of how many items it holds — the list changes often and the file is the only source.
- `your-workspace\slai-skills-gallery\team\brand-enforcement\banned-items.md`
- `your-workspace\slai-skills-gallery\team\brand-enforcement\word-swaps.md`
Check every draft against the current list before it is shown. If the files cannot be read, stop and say so — never proceed on memory.
A guided 3-step read on one question — is this client right for Anne to take on? Scores a prospective client engagement against Anne's practice through the Ikigai lens, pressure-tests the commercial side, and hands back a take-it-or-not recommendation with the single most important question to ask the client before deciding.
## Context Required
Read before running
- `your-workspace\CLAUDE.md` — voice, style rules, no-colon heading rule
- `your-workspace\.claude\projects\C--Users-anne\memory\reference_196_banned_words.md` — banned-word list for the brand pass (path via slai-skills-gallery/team/brand-enforcement/banned-items.md)
- `your-workspace\scripts\html_to_gdoc.py` — renders the final read as a styled SLAI Google Doc
Anne's practice profile is hardcoded below. Do not ask her for it. The only profile input collected each run is current capacity.
## Anne's Practice Profile (hardcoded — the scoring baseline)
**What she offers**
- Empowered Fundraiser — campaign counsel, feasibility studies, and fractional/embedded fundraising (she does the asking, not just advising)
- She Leads AI — AI education programs (CAE, ACA, the Academy), the Society membership, CREATE, Social Saturday, speaking and keynotes
**What energizes her**
- Work at the intersection of fundraising, AI, and women's leadership
- Building something repeatable — a system, a cohort, a framework — not one-off deliverables
- Rooms where she's teaching women to lead with AI, or helping an org find real money for a mission she believes in
- High-trust counsel relationships where she's in the room for the hard decisions
**Her non-negotiables**
- She is counsel and fractional fundraiser for EF — not a CAO, not staff backfill
- No work that requires inflating numbers, telegraphing sensitive campaign topics, or compromising a client's trust
- No engagements that are pure execution grind with no strategy or teaching component
- Capacity-protective — she guards her Einstein hours (5–10am) and won't take work that turns her calendar into someone else's emergencies
> Anne edits this block directly when her practice shifts. It is the only place the baseline lives.
## Steps
### Step 0 — Capacity only
Ask one question before starting: **"What's your current capacity — Open / Partial / Limited / Full?"** Store it for the friction logic. Do not ask about offerings, energizers, or non-negotiables — those are hardcoded above.
### Step 1 — Prospect intake
Ask conversationally, one message, not a form. Let her answer in a paragraph if she wants:
- Who is this? (name, org, or a description)
- How did it come in? (referral, inbound, outbound)
- What do they say they need? (their words if possible)
- What type of engagement? (advisory, workshop, fractional, cohort, speaking, unclear)
### Step 2 — Ikigai scoring
Briefly name the four quadrants, then ask her to score each **1–5**. Present all four at once or one at a time — read her preference.
| Quadrant | Question | 1 → 5 |
|---|---|---|
| What you love | Does this light you up — would you do it even if no one was watching? | Draining → Energizing |
| What you're great at | Does this call on expertise you've actually built — not just things you can figure out? | Out of depth → In my zone |
| What the world needs | Is this a real, urgent problem — not just something they find interesting? | Nice to have → Critical priority |
| What you can be paid for | Are the commercial signals real — budget confirmed, timeline clear, decision-maker engaged? | No signal → Fully confirmed |
After scoring, ask for **one sentence of reasoning per quadrant** (optional, but it sharpens the output).
### Step 3 — Fit signals
Frame as "now let's pressure-test the commercial side." Quick secondary check:
- **Readiness** — Ready to act / Aligned but not moving / Exploring / Unclear
- **Budget** — Confirmed / Allocated / Soft signal / Unknown / Red flag
- **Authority** — Decision-maker / Champion / Gatekeeper / Unknown
- **Timeline** — Urgent (weeks) / Defined (months) / Vague / None
- **Gut/energy** — Want this / Neutral / Draining just thinking about it
- **Non-negotiable flag** — No concerns / One concern worth noting / Hits a non-negotiable
### Step 4 — Generate the read
Compute the recommendation, friction, and The One Question using the logic tables below. Run the brand pass (banned words, no-colon headings, voice). Then deliver **both**:
1. **Chat read** — the full output rendered inline so Anne can act immediately
2. **SLAI Google Doc** — same content rendered through `output-template.html` and `html_to_gdoc.py --account ams`, with the direct link and local path returned
## Output
Both surfaces use this exact structure. The One Question carries the most visual weight.
```
### [CLIENT / PROSPECT NAME] — Ikigai Engagement Read
Recommendation — [SAY YES / SAY YES, BUT CLARIFY FIRST / NOT YET]
[One sentence rationale]
Ikigai alignment — [avg]/5
| Quadrant | Score | Read |
|---|---|---|
| What you love | X/5 | Strong fit / Partial fit / Gap |
| What you're great at | X/5 | Strong fit / Partial fit / Gap |
| What the world needs | X/5 | Strong fit / Partial fit / Gap |
| What you can be paid for | X/5 | Strong fit / Partial fit / Gap |
Friction (only if present, max 2)
- [friction point 1]
- [friction point 2]
—————————————————————————
THE ONE QUESTION
> [the single most important question to ask the prospect before deciding]
```
### Recommendation logic
| Condition | Recommendation |
|---|---|
| Avg ≥ 4.0 AND budget not red flag AND no non-negotiable hit | SAY YES |
| Avg ≥ 3.0 AND no non-negotiable hit | SAY YES, BUT CLARIFY FIRST |
| Avg < 3.0 OR non-negotiable hit | NOT YET |
### Friction triggers (max 2, most important first)
- Budget soft/unknown/red flag → "Budget signal is soft — commercial commitment isn't confirmed."
- Authority not decision-maker → "Buying authority hasn't been confirmed — you may be talking to a champion, not the check-signer."
- Love ≤ 2 → "The energy signal is low — this work may drain rather than fuel you."
- Paid ≤ 2 → "Commercial viability is weak — the financial case needs grounding."
- Capacity = Full → "Your capacity is full — this would need to displace something."
- Gut = Draining → "Your gut says draining. That's data."
### The One Question logic (first that applies)
1. Paid ≤ 2 OR budget unknown/red flag → "What budget has already been approved for solving this, and who specifically has the authority to release it?"
2. Needs ≤ 2 OR readiness = exploring → "What would have to be true for this to become the most urgent thing on their agenda right now?"
3. Love ≤ 2 → "Six weeks into this engagement, which part of the work would you dread on a Monday morning?"
4. Great ≤ 2 → "What specifically do they believe makes you the right person for this — and does that match what you believe about yourself?"
5. Authority ≠ decision-maker → "Who else needs to say yes before this moves forward, and when can you be in the room with them?"
6. Default → "What exact outcome would make this engagement feel unquestionably worth your time and energy?"
### Quadrant read words
- 4–5 → Strong fit · 3 → Partial fit · 1–2 → Gap
## Works With
**Chains upstream from**
- `transcript-processor` / `she-leads-ai-meeting-notes` (OPTIONAL) — if a discovery call was recorded, pull intake answers from the notes instead of asking cold. Without it, Anne answers intake live.
**Chains downstream to**
- `fundraising-correspondence` — a SAY YES feeds a warm follow-up note to the prospect
- `sales-page-builder` / `workshop-maker` — if the read greenlights a productized offer, hand the engagement type forward
**Pairs well with**
- `devils-advocate` — run a SAY YES through it before committing, to stress-test the call
**Standalone mode**
Runs fully standalone. Anne answers intake and scoring live; the skill returns the chat read and the Google Doc with no upstream or downstream connections.
## Gotchas
I know you'll want to ask Anne for her offerings, energizers, and non-negotiables at Step 0 — don't. They're hardcoded above. Ask only for capacity.
I know you'll want to soften a Gap (1–2) score with encouraging language — don't. Name it plainly. This is decision support, not a therapy session.
I know you'll want to hedge the recommendation with "it depends" — don't. Make the call. The logic table gives you the answer; state it.
I know you'll want to bury The One Question in the body — don't. It's the most important part of the output. Give it the most visual weight, set apart, last.
I know you'll want to include all six friction points when several trigger — don't. Max two, most important first. More than two dilutes the signal.
I know you'll want to skip the Google Doc when the chat read "looks done" — don't. Anne chose both surfaces. Always render the doc and return the link.
Add to this list as failures surface.
## Constraints
- No colons in headings or list-label constructions (Anne's house rule) — use em dashes or full sentences
- Run the banned-word and voice pass BEFORE showing either surface — Anne never catches violations
- Never invent budget, authority, or timeline facts the prospect didn't give — score what's there, flag what's missing
- The recommendation is a recommendation — never present it as a final decision Anne must follow
- Capacity = Full never auto-vetoes; it only adds friction and shapes the recommendation through the table
## Check-Ins
After first run, ask
- Are you editing the read? What are you changing?
- Did the recommendation match your gut — or did the logic disagree with you?
Before wrapping up, ask
- Any failure pattern to add to the gotcha section right now?
- What else can I take off your plate?
## Changelog
| Date | Version | What Changed |
|------|---------|-------------|
| 06.24.26 | 1.0.0 | Initial skill. Anne-tailized — practice profile hardcoded, Step 0 reduced to capacity only. Dual output (chat read + SLAI Google Doc). |
Meet the Builder who made this
Anne Murphy
Anne Murphy
Founder & CEO, She Leads AI · Founder & CEO, Empowered Fundraiser Consulting

Anne Murphy is a public speaker, consultant, and serial entrepreneur building a movement of women in AI. She is founder of She Leads AI, co-founder of Moxxee, and CEO of Empowered Fundraiser Consulting, with 35 years in fundraising and more than $10 billion in campaigns. She has educated more than 4,000 women in responsible AI use and is co-author of the Framework for Responsible AI in Fundraising and co-host of The Daily AI Show.