| name | score-accounts |
| description | Score and rank a list of accounts (mixed ZoomInfo company IDs, names, or domains) by ICP fit + buying intent + recent triggers. Returns per-account composite score (0–100), tier (A/B/C), explainable component breakdown (fit / intent / trigger / engagement), a specific "why now" sentence per account, and the working weight set as a saveable search filter set. Resolves name/domain inputs via search_companies with explicit confirmation for ambiguous matches. Iteratively refinable — adjust weights, swap axes, retier, or drill into a specific account. Use for account-based selling, ABM list prioritization, territory planning, sales prospecting prioritization, signal-based selling, buyer intent ranking, B2B prospecting. Triggers on phrases like "score these accounts", "prioritize this list", "rank by ICP fit and intent", "which accounts should I work first", "build a tiered account list". |
Score Accounts
Rank a list of accounts by ICP fit + intent + trigger signals. Calls get_gtm_context(detailed: true) unconditionally, resolves mixed-identifier inputs explicitly surfacing ambiguity, scores each account on four axes, and presents both the ranking and the weight set as iteratively-refinable artifacts.
The bar
- Resolution accuracy 100% — every input auto-resolved / verified / ambiguous / failed. Nothing silently picked.
- Every score explainable — composite is a transparent weighted sum, never an opaque number.
- "Why now" cites a specific signal — not the composite restated.
- Every tier comes with a recommended action.
- Weights and axes are exposed and overridable.
Sellers reject black-box scores. Transparency + per-account "why now" are what make this skill trusted.
Scope
Scores company-level accounts, not contacts. Persona-aware ranking is a chain target via personalize-email after tier-A is produced.
Input
- Accounts (required) — list of ZI IDs / company names / domains / mixed CSV.
- Use case (default
prospecting) — prospecting, abm, territory_planning, pipeline_acceleration. Affects tier thresholds + recommended actions.
- Weight overrides (optional) —
{fit, intent, trigger, engagement} summing to 100.
- Tier thresholds (optional) —
{A, B}. C is the remainder.
- ICP override (optional) — natural-language refinement on top of
get_gtm_context.icp.
- Intent topics (optional) — explicit list overriding GTM-derived defaults.
Four-axis framework
| Axis | Question | Source |
|---|
| Fit | Does this match our ICP? | enrich_companies vs get_gtm_context.icp |
| Intent | Are they actively researching the topic? | enrich_intent with curated topics |
| Trigger | Fresh event creating a window? | enrich_news + enrich_scoops (last 90d) |
| Engagement | Already interacting with us? | account_research narrative for known accounts. If absent, weight redistributed. |
Each axis 0–100 independently. Composite is the weighted sum — never collapsed to an opaque number.
Default weights
fit: 45%
intent: 25%
trigger: 25%
engagement: 5% (redistributed if unavailable)
User overrides accepted. Weights are exposed in every output. Cache per-axis scores; recompute only the composite when weights change.
Tier thresholds
| Tier | Composite | Recommended action |
|---|
| A | ≥ 75 | Route to AE for 1:1 outreach within 24h. Chain to personalize-email. |
| B | 50–74 | SDR sequence; ABM retargeting; nurture-to-meeting. |
| C | < 50 | Watchlist; monitor for tier-promotion signals. |
Use-case adjustments: abm → A=80/B=55 · territory_planning keeps defaults · pipeline_acceleration → A=65/B=40.
Workflow
1. Pull GTM context (always)
get_gtm_context(detailed: true). Capture ICP, personas, competitors, offerings, strategic priorities. ICP = fit-axis target; strategic priorities → intent-topic curation.
2. Honor input data first
Use user-supplied weights / thresholds / ICP refinements / intent topics. Fall back to GTM defaults only for missing fields.
3. Resolve identifiers (four-bucket routing)
- Auto-resolved — top match dwarfs alternatives. Score without confirmation.
- Verified — clear top match BUT plausible alternatives exist. Score; surface verification note.
- Ambiguous — no dominant match. Pause scoring; surface candidates.
- Failed — no match. List separately.
Routing by input type:
- Numeric ZI ID → auto-resolved.
- Domain (
.com / .io / .co / .ai) → search_companies(companyWebsite). Single match → auto-resolved. Multiple → ambiguous.
- Name →
search_companies(companyName).
- Top match's size/revenue dwarfs alternatives → auto-resolved.
- Clear top but 3+ plausible alternatives → verified with note.
- No dominant match → ambiguous.
- No match → failed.
Surface rule. Never silently pick a winner. Present top 5 with attributes; ask user to confirm. Use GTM context as soft tiebreaker for verified (e.g., a B2B SaaS context defaults an ambiguous name to the SaaS-industry candidate over an unrelated-industry candidate, with a flag).
Domain-confirmation gate (mandatory for high-collision names). When search_companies(companyName=X) returns >100 matches AND no strong GTM tiebreaker exists, require domain confirmation. Surface top match's domain and ask. Never silently auto-pick — cost of getting it wrong is scoring the wrong company entirely.
Duplicate-record detection (mandatory). If top candidates share the same domain root (e.g., acmeco.com and acmecoinc.com) AND ≤20% revenue diff AND same metro/country → flag suspected duplicate. Surface both records and offer to union. For signal-heavy workflows, scoring both and unioning is the right default — signals may be split across records.
Resolution path must hit 100% accuracy. Score auto-resolved + verified immediately; pause ambiguous; list failed separately.
3.5. Relationship-context pre-flight (mandatory)
Tag each resolved account against GTM context. Tag visible on the row before the tier letter — sellers see relationship status BEFORE running the play.
competitor ⚔️ — in get_gtm_context.competitors. Don't exclude from ranking (competitive intel matters) but make it impossible to miss visually.
customer 🤝 — in get_gtm_context.customers / proof_bank. Shift recommended action to expansion / renewal.
partner 🔗 — in get_gtm_context.partners / integration_partners. Shift to co-sell / integration angle.
prospect — default; no tag.
In the row label: ⚔️ [Account] (B 62). Skill never silently produces "pursue this competitor" rankings.
4. Curate intent topics
From get_gtm_context.strategicPriorities (or user-supplied list), derive 5–10 topics. lookup intent-topics fuzzyMatch=<theme> — one call per theme (multi-field fuzzyMatch fails silently). If no topics resolve, set intent weight = 0 and redistribute.
5. Fetch data per account (parallel, batched ≤10; chunked for large lists)
For each resolved account, in parallel:
enrich_companies(companyId, fields: industries, employeeCount, revenue, country, metroArea, businessModel, employeeCountByDepartment, foundedYear).
enrich_intent(companyId, topics: curated list, signalScoreMin: 60, signalStartDate: 30d ago, pageSize 25).
enrich_news(zoominfoCompanyId, last 90d, categories: PERSON,MERGER_OR_ACQUISITION,FUNDING,PRODUCT,FINANCIAL_RESULTS, pageSize 15).
enrich_scoops(zoominfoCompanyIds, last 90d, pageSize 10).
Hard batch limit: ≤10 concurrent per MCP tool type.
Batch + context-window discipline. For lists >25 accounts, process in chunks of ~25 accounts end-to-end (resolve → fetch → score → compose row → write chunk → discard raw payloads) before moving to the next chunk. Don't accumulate full raw enrichment payloads for hundreds of accounts in working context — once per-axis scores + the winning trigger event + the winning intent topic are captured per account, drop the rest. For >100-account lists, summarize completed chunks into running totals (tier distribution, top-A list, multi-product anomalies, duplicate-suspected flags, missing-axes counts) and discard the per-account breakdowns from context. Output is built incrementally chunk-by-chunk so a long list doesn't blow context.
Skip account_research here; fire selectively in §7.5 for tier-A.
6. Score each axis
Fit (0–100) — compare enrich_companies to get_gtm_context.icp:
| Dimension | Max | Banded scoring |
|---|
| Industry / sub-industry | 25 | Primary = 25 · secondary = 15 · adjacent = 8 · none = 0 |
| Employee count band | 20 | In band = 20 · one off = 12 · two off = 4 · outside = 0 |
| Revenue band | 20 | Same banding |
| Geography | 15 | ICP country = 15 · in continent = 8 · outside = 0 |
| Business model | 10 | B2B/B2C match = 10 · mixed = 5 · mismatch = 0 |
| Technographic (optional) | 10 | Uses named tech-stack vendor = 10 · else 0. Verify via search_contacts + techAttributeTagList if needed. |
Cache per account; reuse across weight changes.
Intent (0–100) — max(signalScore × audienceStrengthFactor) from enrich_intent. A=1.0 · B=0.85 · C=0.7 · D=0.55 · E=0.4. Cap 100. Record winning topic for "why now." If no data → 0 with "no intent activity in window" flag.
Trigger (0–100) — for each event in enrich_news + enrich_scoops (last 90d):
event_score = signal_type_weight × recency_factor
| Signal type | Weight |
|---|
| M&A, Funding, New CEO/C-suite hire | 95 |
| Product launch, Hiring surge, Earnings beat/miss | 75 |
| Partnership, New facility | 55 |
| Pain-point scoop, Other PERSON moves | 45 |
| Generic press release | 25 |
Recency: 0-14d=1.0 · 14-30d=0.7 · 30-60d=0.4 · 60-90d=0.2 · >90d=0.
Account trigger = max(event_score) capped at 100. Record winning event for "why now."
Engagement (0–100) — if account_research returns rich CRM context: active deal/renewal/champion = 80–100 · past meeting/known stakeholder = 40–70 · no history = null. If null, redistribute weight and surface gap.
7. Compute composite + assign tier
composite = round((fit × w_fit + intent × w_intent + trigger × w_trigger + engagement × w_engagement) / 100)
Assign per thresholds. Default A≥75 / B 50–74 / C<50 (use-case overrides apply).
7.5. Auto-pull account_research on tier-A rows (mandatory)
Tier A = "route to AE in 24h." Engagement-axis gap on tier-A is the highest-cost gap to close.
For each tier-A account (and ONLY tier-A — cost control): account_research(zoominfoCompanyId, query="Open opportunities, active deal stages, named champion or blocker, last activity date, renewal timing"). Parse for:
- Open deal status — stage, value, next step.
- Renewal date — surface prominently if within 90 days.
- Named champion / blocker — source-tag
[from account_research].
- Last activity — flag if >60 days old.
Append inline beneath the why-now:
| 1 | [Account] | 🤝 A | 84 | ... | [Trigger event] X days ago — [pain-bridge]
↳ Engagement: open deal $XXXk, champion [Name], last activity Xd ago [from account_research]
If no CRM history → annotate "no engagement signal — cold open."
For tier-B/C: skip — cost-to-value doesn't justify.
8. Compose "why now" per account
One sentence anchored on the strongest signal:
- Trigger + in-tier fit → cite event + date. "Closed [counterparty] acquisition 20 days ago."
- High intent → cite topic + score + recency. "Spiked on '[topic]' (score 92, audience A) over 14 days."
- Strong fit, no fresh signal → "Perfect-fit ICP — no fresh trigger; pursue on fit alone."
- Engagement-driven → "Active deal in flight; renewal due in 47 days."
- Strong trigger BUT C-tier (fit mismatch) → be explicit about routing: "Do not pursue — strong trigger (new CEO 10 days ago) but ICP mismatch ([reason]) keeps this low priority." Don't bury the trigger; surface BOTH signal and recommendation.
- Low signal across all axes → "Low signal — monitor only."
Never restate the composite as the why-now. Always cite the underlying axis driver.
9. Self-check before output
- ☑ Composite shown with component breakdown (fit / intent / trigger / engagement).
- ☑ "Why now" cites a specific signal, not the composite.
- ☑ Tier has a recommended next action.
- ☑ Weights + axes used exposed.
- ☑ Every input bucketed (resolved / ambiguous / failed) — none silently dropped.
- ☑ Ambiguous surfaced, not silently picked.
- ☑ Stale signals (>90d) contribute 0; not padded.
- ☑ Missing axes flagged + weights redistributed transparently.
- ☑ Iteration options offered.
10. Present + offer iteration
- Accept ranking; save filter+weight set.
- Adjust weights — re-rank without recomputing axes.
- Tighten / loosen tier thresholds.
- Refilter — remove tier C / specific industries.
- Swap ICP — different ICP definition.
- Drill into one account — chain to
personalize-email.
- Add accounts — extend list and re-score.
Re-execute step 5 only when account list changes. For weight / threshold / ICP changes → recompute from cached axis scores.
Terminate when user accepts, saves, or hands off.
Anti-patterns — fail-fast checklist
- Black-box composite — single number without component breakdown.
- "Why now" = composite restated.
- Silent identifier resolution on ambiguous names.
- Fixed weights not exposed.
- Tier without action.
- Stale signal padding — events >90d contributing.
- Generic "why now" — "good fit" applies to every account.
- Ignoring missing axes — pretending engagement exists when null.
- Auto-accepting ambiguous matches.
- No iteration affordance.
Fallback rules
get_gtm_context empty → use user-supplied ICP override; surface gap.
- Intent topics fail to resolve → intent weight = 0; redistribute.
enrich_intent empty → score = 0 (real signal, not gap).
enrich_news + enrich_scoops both empty → trigger = 0; flag.
- Engagement unavailable → weight = 0; redistribute proportionally.
- All axes thin → tier C "monitor only"; honest.
- Resolution failure → list separately; never silently drop.
Never block ranking on a single missing axis. Never invent data.
Output Format
TL;DR — Account Scoring · N accounts · Pass [M]
Use case: [restate]. Weights · Thresholds A≥[X] · B[Y–Z].
Resolution: [R resolved · A ambiguous · F failed]. [If A>0: "User confirmation required."]
Tier distribution: A: x · B: y · C: z.
Top 3:
- [Account] (tier · composite) — [why now]
- ...
Resolution Summary
| Input | Resolved To | ZI ID | Confidence | Status |
|---|
Status legend: ✅ Auto-resolved · 🔍 Verified · ⚠️ Ambiguous · ❌ Failed.
Ambiguous matches — please confirm: [list top 5 candidates per ambiguous input with attributes].
Ranked Accounts
Sorted by composite descending. Engagement column – when redistributed.
| # | Account | Tag | Tier | Composite | Fit | Intent | Trigger | Eng | Why now | ZI ID |
(Tier-A rows also carry an "↳ Engagement: ..." sub-line from §7.5.)
Weights & Axes Used
fit: [%]
intent: [%]
trigger: [%]
engagement: [%] (redistributed if axis unavailable)
Axes missing this run: [list, or "none"].
Recommended Actions per Tier
- Tier A — Route to AE for 1:1 outreach within 24h. Chain to
personalize-email.
- Tier B — SDR sequence; ABM retargeting; cadence with the why-now as opener.
- Tier C — Monitor; re-score weekly.
Iteration Options
- Accept ranking; save filter+weight set.
- Adjust weights.
- Tighten thresholds.
- Refilter.
- Swap ICP.
- Drill into one account.
- Add accounts.
Caveats (when relevant)
- Ambiguous pending — N accounts not yet scored.
- Failed resolutions — N inputs had no match.
- Engagement axis unavailable — surface per-account (
no CRM signal — consider cross-check) for each tier-A row.
- Intent topic curation per-tenant — if <50% of curated topics resolve, intent axis is configuration-gap, not signal-absent.
- Intent thin — <3 topics resolved; intent directional.
- Stale-signal cliff — N accounts' best trigger >60d old.
- Edge-of-recency — N trigger events 80–90d.
- GTM-context gap —
icp sparse; fit-axis precision reduced.
Final Filter + Weight Set (on accept)
{
"icp": { },
"weights": {"fit": 45, "intent": 25, "trigger": 25, "engagement": 5},
"tier_thresholds": {"A": 75, "B": 50},
"intent_topics": ["..."],
"use_case": "prospecting",
"_meta": {"account_count": ..., "tier_distribution": {...}, "axes_missing": [...], "pass_count": ...}
}
Chain Targets
personalize-email per tier-A contact → grounded in the same "why now" signal.
build-list to extend the universe.
find-similar on a tier-A seed.
tam-sizer with this filter set to confirm universe size.