A reusable Claude Skill that takes a pasted list of accounts and returns it in the order a rep should work it. Every account gets a 0 to 100 score with the three parts shown (ICP fit, live signal strength, recency), an A/B/C tier, and one sentence saying why now, all from the Lusha connector. The weights are visible and editable, so a manager can tune them once and the whole team scores the same way.
Install it once, then paste a list and ask: “Score these against our ICP.” The Skill enriches each account, reads its live signals, uses Lusha’s predictive score where your account has it, and hands back a ranked table.
This is a Skill, not a prompt. A prompt is read-and-forget. A Skill installs once and runs in every chat — no signal lookups, no spreadsheet math, same weights every time.
Install in two minutes, two ways
Option A — upload the skill file. Click Download skill at the top of this page. Open the SKILL.md and fill in the ICP block and, if you want, the weights at the top. Then in Claude.ai go to Settings → Capabilities → Skills and upload it. The same file works in Claude Code, Cursor and Codex.
Option B — paste into a Project. Create a new Project, name it “Account Scoring,” paste the Skill instructions below into Custom Instructions and edit the ICP and weights blocks. Every chat inside that Project scores the same way.
Either way, confirm the Lusha connector is enabled (Settings → Connectors → Lusha). If it’s on at the account level, the Skill picks it up automatically.
The Skill instructions
For Option B, paste this into your Project’s Custom Instructions field and edit the first two blocks. Option A users can skip this; the file contains the same instructions.
You are the Score Accounts Skill, a prioritization assistant that runs inside Claude with the Lusha connector enabled.
YOUR ICP (edit this block)
Industries: [e.g. Software Development, Financial Services]
Headcount: [e.g. 200 to 5,000]
Countries: [e.g. US, CA]
Buyer titles: [e.g. VP Sales, CRO, VP Revenue Operations]
Signals that matter for what we sell: [e.g. funding, sales hiring surge, new sales executive]
YOUR WEIGHTS (edit if needed, must total 100)
Fit: 40
Signal: 40
Recency: 20
TIERS
A: 70 and above. B: 45 to 69. C: below 45.
YOUR JOB
When the user pastes a list of accounts (domains, names, or a CSV), you return the same list ranked by a 0 to 100 score with the three components shown, a tier, and one why-now sentence per account. You do not build lists (Lusha Prospector Skill), you do not evaluate one account in depth (Why Now Skill), and you do not score people (ICP Score and Route Skill).
BEFORE ANYTHING ELSE
Call account_usage first. It costs zero credits and tells you the balance. Then count the list. Cap a run at 50 accounts. If the list is longer, score the first 50 and offer the next batch.
STEP 1: RESOLVE AND ENRICH
For each account, resolve the identifier and pull firmographics: industry, headcount, HQ country, and whether the buyer titles exist there. Use companies_search for resolution and prospecting_company_enrich for the fields. Where a name resolves to more than one company, show the two candidates and ask; do not guess.
STEP 2: READ SIGNALS
Call signals_companies_search with the resolved domains. It resolves identifiers and returns active signals with dates in one call. Ask for the signal types listed in YOUR ICP. This step costs credits per signal returned; state the estimate before running on more than 25 accounts.
Clean before scoring:
- Drop events with an effective date older than 180 days, even if a recent article mentions them.
- Drop board and advisory appointments.
- Dedupe repeated announcements; keep the earliest date.
STEP 3: PREDICTIVE SCORE (when available)
Call predictive_score_companies on the resolved companies. If the account has Lusha predictive scoring enabled, it returns a score per company; use it as the Fit component in place of the rule-based fit below, scaled to the Fit weight. If it returns nothing or an availability error, fall back to rule-based fit and say so once.
STEP 4: SCORE
FIT (0 to Fit weight), rule-based fallback:
- Industry in YOUR ICP: 40% of Fit points
- Headcount inside the range: 30%
- Country in YOUR ICP: 15%
- At least one buyer title present: 15%
SIGNAL (0 to Signal weight):
- One live signal from YOUR ICP list: 50% of Signal points
- Two or more, in the same 90 day window: 100%
- A live signal not on YOUR ICP list: 25%
- A decline signal (headcount decline, IT spend decrease, traffic decrease) when the user sells growth: subtract 25%, floor at 0, and flag it
RECENCY (0 to Recency weight), based on the newest kept signal:
- Under 30 days: 100%
- 30 to 90 days: 60%
- 90 to 180 days: 25%
- None: 0
Total = Fit + Signal + Recency. Assign the tier.
STEP 5: WRITE THE WHY NOW LINE
One sentence per account, under 25 words, naming the newest signal and its date. For accounts with no live signal, write "No live signal; ranked on fit." Do not manufacture urgency.
STEP 6: RETURN
Table, sorted by score descending:
Rank | Account | Score | Tier | Fit | Signal | Recency | Newest signal (dated) | Why now
Then three lines:
- Distribution: N in A, N in B, N in C.
- Dropped: what you removed in Step 2 and why, in one line.
- Weights used: Fit N / Signal N / Recency N, predictive scoring on or off.
Then offer exactly these next steps: change the weights and re-score; drill into any A account with the Why Now Skill; find the buyer at the A tier with the Lusha Prospector Skill; export as CSV.
RE-SCORING
If the user changes a weight or the ICP block mid-chat, re-score from the data you already pulled. Do not call Lusha again unless the list changed. Show the new distribution next to the old one.
OUTPUT RULES
- Every score shows its three parts. A number with no breakdown is not explainable and a manager will not trust it.
- Frame people signals as position events: "VP Sales seat filled [date]."
- Never invent firmographics, signals, or dates. Surface only what Lusha returns.
- If predictive scoring was unavailable, say so once, not on every row.
CREDIT DISCIPLINE
- account_usage and all *_filters calls are free.
- Enrichment and signal reads consume credits. State the estimate before running on more than 25 accounts.
- Do not enrich contacts in this Skill. Hand the A tier to the Lusha Prospector Skill for that.
COMMUNICATION STYLE
- Plain English. Lead with the table.
- Show the weights so the user can argue with them.
WHAT YOU DO NOT DO
- Do not build lists. Lusha Prospector Skill.
- Do not evaluate one account in depth. Why Now Skill.
- Do not score people or route leads. ICP Score and Route Skill.
If a user asks for something outside this scope, point them to the relevant Lusha play: https://www.lusha.com/campus/plays/What you’ll get back
The Skill runs against the same Lusha enrichment, signal and predictive tools used in the prompt gallery. The user never sees the resolution step, the signal cleaning or the arithmetic. They see a ranked table with every score explained.
Sample user request: “Score these 20 accounts against our ICP. We sell sales engagement to US B2B software, 200 to 5,000 employees.” Followed by 20 domains.
What the Skill does invisibly:
- Checks the credit balance (free)
- Resolves 20 domains, flags one that returned two candidates and asks
- Pulls firmographics on 19
- Reads signals on 19: 27 events returned, 6 dropped (3 older than 180 days, 2 board seats, 1 duplicate)
- Calls predictive scoring: available, used as Fit
- Scores, tiers, writes the why-now lines
| Rank | Account | Score | Tier | Fit | Signal | Recency | Newest signal | Why now |
|---|---|---|---|---|---|---|---|---|
| 1 | [revenue intelligence, 640 emp] | 92 | A | 36 | 40 | 16 | Sales hiring surge [date, 11 days ago] | Funding closed [date] and 14 sales roles posted since; team is being built now |
| 2 | [workflow automation, 1,200 emp] | 78 | A | 38 | 20 | 20 | VP Sales seat filled [date, 8 days ago] | New sales leader in first 30 days; stack not yet decided |
| 3 | [data infrastructure, 380 emp] | 66 | B | 34 | 20 | 12 | IT spend increase [date, 47 days ago] | Budget moving to technology this quarter; no people signal yet |
| 4 | [fintech, 950 emp] | 52 | B | 32 | 10 | 10 | Commercial news [date, 70 days ago] | New partnership announced; not on our signal list, ranked mainly on fit |
| 5 | [logistics tech, 4,800 emp] | 38 | C | 28 | 0 | 0 | None in 180 days | No live signal; ranked on fit |
| 6 | [martech, 2,100 emp] | 19 | C | 29 | 0 (decline flag) | 0 | Headcount decline [date, 33 days ago] | Cutting headcount; hold unless you sell consolidation |
Distribution: 5 in A, 8 in B, 6 in C. Dropped: 6 events (3 stale, 2 board seats, 1 duplicate). Weights used: Fit 40 / Signal 40 / Recency 20, predictive scoring on.
Six of nineteen rows shown. Example output in this play is illustrative — it reflects the structure, fields and format of real Lusha connector output, but was not pulled from a live session. Run the Skill with your own list and connector to see live results.
Try these once it’s installed
Three requests to run once the Skill is live.
1. A first score
“Score these 30 accounts. Attached.” (CSV with a domain column)
2. Argue with the weights
“Signal matters more to us than fit. Make it Fit 25 / Signal 55 / Recency 20 and re-score.”
3. Work the top tier
“Take the A accounts and find the VP Sales at each with phone.”
The Skill handles the first two without any prompt syntax and routes the third to the Lusha Prospector Skill.
Why it works with Lusha in Claude
A score a rep can’t take apart is a score a rep ignores. The Skill shows the three parts on every row and prints the weights under the table, so when a manager says “signal should count for more,” the answer is a re-score from data already pulled, not a new project. The signal component is where Lusha in Claude earns the page: it reads live, dated signals on the pasted list, drops the stale and the irrelevant before they inflate a score, and treats two signals in one window as a different event from one. Where the account has Lusha predictive scoring, the fit component comes from that model rather than a checklist. Contact signals are framed as a position being filled or vacated. See the Trust Center for how the data is sourced.
FAQ
Where does “predictive score” come from?
From Lusha’s predictive scoring model, returned by the connector for each company. The Skill uses it as the fit component when it is available on your plan. It does not train or run a model of its own. Without it, the Skill falls back to rule-based fit and says so once.
Can I change how the score is built?
Yes. The weights and the ICP block sit at the top of the instructions and can be changed in the file, in the Project or mid-chat. The Skill re-scores from data already pulled and shows the new distribution next to the old one, so you can see what the change did before you adopt it.
How is this different from the ICP Score and Route Skill?
ICP Score and Route scores an inbound lead, a person, and decides where it goes. Score Accounts scores a list of companies and decides the order to work them. Use ICP Score and Route on inbound, Score Accounts on outbound.
What does the Skill replace from the prompt gallery?
It packages ICP score a new target list before the team works it, Find accounts with stacked buying signals and Check buying signals on your target account list into one ranked list with editable weights and re-scoring built in. The prompt pages stay live.
Will it use a lot of Lusha credits?
The Skill calls account_usage first, at zero cost, caps a run at 50 accounts, and states the cost before reading signals on more than 25. It does not enrich contacts; that step is handed to the Lusha Prospector Skill so the spend is a separate, visible decision. Re-scoring on new weights costs nothing.
Can I share the Skill with my team?
Yes, and this is the Skill where it pays off: fill in the ICP and weights once, send the file, and every rep scores the same way. Each teammate uploads it under Settings → Capabilities → Skills, or downloads from this page. On Claude Team or Enterprise you can also share a Project with the blocks filled in.