Tech Stack Snapshot

Tech Stack Snapshot

Per-company tech-stack snapshot grouped by category, with displacement angles for competitive tools and integration angles for partner tools — anchored on the user's GTM context. Resolves mixed-identifier inputs, queries search_companies with techAttributeTagList to check each product in a curated universe, and presents both the detected stack and the gaps honestly.

How it works

search_companies accepts techAttributeTagList (tech-product IDs) as a filter:

search_companies(  companyId="<input IDs, comma-separated>",  techAttributeTagList=<one product ID>,  pageSize=<N>) → returns subset of input companies that have that product tagged

Iterate over a curated universe of ~30–50 high-relevance tech products → build a company × product matrix → group by category and pair with GTM-context-anchored plays.

The bar

1. Resolution accuracy 100% — every input bucketed; never silently picked.
2. Detections are binary and verified — ✅ comes from a non-zero search_companies result; ❌ means no tag. Never invent presence.
3. Output is grouped by category.
4. Recommended plays anchor on GTM context.
5. Coverage gaps surfaced honestly — absence = "no tag detected", not "no tool used."

Always-on context: get_gtm_context

Every run calls get_gtm_context(detailed: true). Drives:

• Which categories are in scope (sales-focused vs. dev-focused).
• Which detected tools map to displacement vs. integration angles.
• Framing of recommended plays (anchored on specific value props).

Scope

Snapshots are company-level. Per-person tech-skill data is out of scope.

Input

• Companies (required) — list of ZI IDs / names / domains / mixed CSV.
• Categories of interest (optional) — any of: sales, marketing, analytics, data, conversation_intelligence, intent_abm, cdp, devops, security, customer_service, collaboration. Default = first 7 (B2B SaaS sales motion).
• Custom universe (optional) — ["product_id_1", ...] to override curated default.
• Use case (default sales_prep) — sales_prep, battle_card, integration_partner_research, displacement_targeting. Affects play framing.

The curated universe (default)

~30 anchor products across 7 categories. The skill resolves vendors and products at runtime via lookup — see §3.5 below for the canonical enumeration paths. The default anchor set:

Always include both generic vendor IDs AND specific sub-products — companies tagged with the generic ID won't surface if only sub-products are checked. Salesforce has 70+ tagged products; the universe must include each vendor's major sub-products.

User can extend / narrow per run.

Enumerating the full tech taxonomy via lookup

The orchestrator does NOT need to memorize ZoomInfo's tech taxonomy — every list is enumerable from lookup at runtime. Three calls give you the entire surface area:

Use this path when the user asks "what categories of tech does ZI track?" / "what vendors exist in the [X] category?" / "what are all the products for [vendor]?" — and when extending the universe beyond the default 7 categories without hardcoding new entries.

lookup quirk to respect: multi-field requests with per-field fuzzyMatch can silently fail on the second field. Call once per fieldName when using fuzzyMatch.

Workflow

1. Pull GTM context (always)

get_gtm_context(detailed: true). Capture competitors (displacement framing), offerings (integration framing), strategic priorities, ICP (sanity-check).

2. Honor input data first

Use user-supplied categories / custom universe / use case. Default only for missing fields.

3. Resolve identifiers (four-bucket routing — same as score-accounts)

• Numeric ZI ID → auto-resolved.
• Domain → search_companies(companyWebsite). Single match → auto-resolved. Multiple → ambiguous.
• Name → search_companies(companyName). Dominant top match → auto-resolved. Clear top with plausible alternatives → verified. No dominant winner → ambiguous.
• No match → failed.

100% resolution accuracy. Probe only resolved + verified rows.

Domain-confirmation gate (mandatory for high-collision names). When search_companies(companyName=X) returns >100 matches AND no strong GTM tiebreaker, require domain confirmation. Never silently auto-pick — the cost is wasted MCP calls AND misleading output.

Duplicate-record detection (mandatory). If two+ candidates share same domain root, ≤20% revenue diff, AND same metro/country → flag suspected duplicate. Probe BOTH records and union the detections — tags may be split across entries (record A might have Salesforce; record B might have HubSpot). Annotate [from A] / [from B] in the output.

Probing one record and reporting "no detections" is the failure mode this rule prevents.

4. Build the product universe

For each category in scope:

• lookup tech-vendors fuzzyMatch=<vendor> — one call per anchor vendor (multi-field fuzzyMatch is unreliable). For category-wide expansion, use lookup tech-vendors with a category or parentCategory filter instead of fuzzyMatch — returns the full vendor list for that category.
• lookup tech-products vendor=<resolved-vendor-name> — returns the vendor's full product catalogue; select anchor products by name match. Requires at least one of vendor, category, or parentCategory.
• Aggregate to {product_id, product_name, category, vendor}.

To enumerate the full tech taxonomy (categories → vendors → products) instead of hardcoding, see the table in "Enumerating the full tech taxonomy via lookup" above.

If custom universe supplied, skip this step; attach category metadata for grouping.

5. Probe each product against the input company list

For each product ID, run one batched call (not one-per-company):

search_companies(  companyId="<resolved IDs, comma-separated>",  techAttributeTagList=<product-id>,  pageSize=<N>)

Cache per (product × company) into a matrix.

Batch limit: ≤10 concurrent search_companies calls. For 30 products, 3 sequential batches of 10.

6. Build per-company snapshots

For each company:

• Group detections by category.
• Multi-product anomaly. If ≥3 products in the same category are tagged (Marketo + Pardot + Marketing Cloud), surface "multi-product anomaly" flag. Don't pick a "primary." Common causes: multi-BU, stale tagging from acquisitions, ZI overlap. Surface so the user investigates.
• Stack signature. Top 4-5 detected tools as a short label (Salesforce + Marketo + Snowflake + Mixpanel). If <3 detections, label "sparse — likely incomplete coverage."
• Identify coverage gaps — categories with no detected product.
• Size vs. universe mismatch. If employeeCount < 50 AND universe is enterprise-default, surface: "small company / enterprise universe — default universe may be blind to SMB tools (Pipedrive, Mailchimp, Zoho). Recommend switching to SMB universe or extending."

7. Map to displacement / integration angles

For each detected tool, apply the GTM-context-anchored angle library:

• In get_gtm_context.competitors → displacement angle anchored on a GTM offering / value prop.
• In get_gtm_context.offerings.integration_partners → integration angle.
• Neither → neutral note; don't fabricate.
• Category gap mapping to a GTM offering → opportunity flag (e.g., "No intent/ABM tool detected — greenfield for [the matching GTM-context offering]").

8. Self-check before output

• ☑ Resolution buckets clean.
• ☑ No fabricated detections (every ✅ from a non-zero search_companies result).
• ☑ Detections grouped by category.
• ☑ Stack signature surfaced (or "sparse" label).
• ☑ Coverage gaps explicit.
• ☑ Plays anchored on GTM context (not generic).
• ☑ "What we didn't check" caveat included.
• ☑ Stale-tag caveat included.
• ☑ Iteration options offered.

9. Present + offer iteration

1. Accept — save universe + snapshot.
2. Extend the universe — add products/vendors.
3. Drill into a category — broaden the product list.
4. Drill into a company — full vendor-by-vendor detail or run account_research for deal-context layered on top.
5. Switch use case — battle-card / integration-partner-research / displacement-targeting.
6. Chain to personalize-email for a contact at a detected-competitor account.

Anti-patterns

1. Fabricating tech presence. Never claim a tool is present if search_companies returned 0.
2. Overclaiming coverage. Default universe is ~30–50 of thousands of products; say so.
3. Absence-as-evidence-of-no-tool. "No tag detected" ≠ "company doesn't use this." Could be data gap, recent adoption, or non-standard naming.
4. Generic displacement angles. "We're better than Salesforce" is not a play. Every angle anchored on GTM context.
5. Flat product list. Category grouping is mandatory.
6. Single-product vendor check. Salesforce has 70 tagged products — the universe must include each vendor's major sub-products.
7. No GTM context → block the run; skill can't produce plays.
8. Silent auto-pick on ambiguous resolution.

Fallback rules

• get_gtm_context empty → continue with detections only; suppress angle library; surface "no GTM context — generic angles only."
• Vendor lookup fails for a category → drop that vendor; flag.
• All products return 0 for a company → "No tag matches in the universe checked. Could be ICP-mismatch (too small / wrong industry) or a data gap. Recommend manual verification."
• Ambiguous resolution → pause; never silently pick.
• Failed resolution → list separately.

Output Format

TL;DR — Tech Stack Snapshot · N companies · Pass [M]

Use case: [restate]. Universe: [N products across M categories].

Resolution: [R resolved · A ambiguous · F failed].

Coverage snapshot:

• Most-detected category: [e.g., "CRM (3 of 3 companies)"]
• Most-frequent product: [e.g., "Salesforce: 2 of 3"]
• Notable gap: [e.g., "Intent/ABM detected at 0 of 3 — greenfield for [matching offering]"]

Resolution Summary

(Four-bucket framework as in score-accounts.)

Per-Company Snapshots

For each resolved company:

## [Company Name] · ZI ID [id]Stack signature: [tool] + [tool] + [tool] + [tool]
By category:- CRM:                ✅ [Detected]  · ❌ [Not detected — list products checked]- Marketing Auto:     ✅ [Detected]  · ❌ [Not detected]- Sales Engagement:   — ([products checked]: no tag)- Data Warehouse:     ✅ [Detected]  · ❌ [Not detected]- BI / Analytics:     ✅ [Detected]  · ❌ [Not detected]- Conversation Intel: — ([products]: no tag)- Intent / ABM:       — ([products]: no tag) ← gap- CDP:                — ([products]: no tag)
Recommended plays:- [Detected tool] (integration partner / displacement): [GTM-context-anchored angle].- [Category gap]: [opportunity framing tied to a GTM offering].
Caveats:- N products across M categories checked.- Absence = no tag in ZI; could be data gap or non-standard naming.- ZI tech-tagging refreshes on cycles; some tags may be 6+ months stale.

Cross-Company Comparison (when N > 1)

Universe Reference

Iteration Options

1. Accept — save universe + snapshot.
2. Extend the universe.
3. Drill into a category.
4. Drill into a company.
5. Switch use case.
6. Chain to personalize-email for a detected-competitor account.

Caveats (when relevant)

• Universe scope — N products / M categories. Not exhaustive.
• Absence is absence. No tag ≠ "doesn't use." Could be data gap, recent adoption, non-standard naming.
• Stale-tag risk. ZI tech-tagging refreshes on cycles; cross-check for high-stakes deal contexts.
• Vendor resolution failures. Any vendor that failed lookup is excluded from the universe; flag separately.
• GTM-context gaps. Sparse competitors / offerings → generic angles. Recommend richer GTM context.

Chain Targets

• score-accounts on the same list with technographic-weighted fit.
• personalize-email for a contact at a detected-competitor account — anchor on the displacement angle.
• find-similar on a company with a strong stack — find more accounts with the same signature.
• account-research to pair technographics with deal narrative.