anysite-crm-score

CRM Score

Deterministic-ish prioritization: explicit rubric, evidence per company, score written to exactly one mapped field.

Prerequisites

Active CRM connection. Profile must map a score target field with mode: overwrite (scores are re-computed by design). Not mapped → offer to store nothing and just report, or send the user to re-run /anysite-crm-setup. The Writing rules in anysite-crm-setup apply to every write. Cap a scoring run at ~50 companies and state the credit estimate (evidence calls × price) before fetching; more → propose tiers or a narrower list.

Flow

1. Fix the rubric BEFORE fetching data

Get ICP criteria from the user, or derive them with anysite-crm-lookalikes logic from closed-won records. Turn them into a written rubric with weights, e.g.:

industry match (0-3), size band (0-2), geo (0-1), funding stage (0-2),
hiring in buyer function (0-1), tech/context signal (0-1)  → 0-10

Show the rubric, get a nod. The rubric goes into the report verbatim — scores must be explainable and reproducible.

2. Fetch evidence (cheap-first)

crm_query_records(object_type="companies", ...) → record_id, name, domain, existing fields

• Base firmographics: search_sql_companies by website — default one domain per call; OR-DSL batching ({website: "a.com|b.com|...", count: 10× domains}) is an optimization with a verification tax (see the anysite-mcp resolve recipe). Never count: 1 — the search is substring match, and a common-token domain comes back with only look-alikes even in a single-domain call. Verify the exact website match per domain via query_cache with an explicit limit (default is 10 — a 20-domain batch needs more). Unverified match = no evidence, score that criterion "unknown"; a domain that never comes back exact-matched is resolved via webparser/parse on the site itself, per the same recipe.
• Stage/funding (only if the rubric needs it): take the alias from crunchbase_link, which the domain-resolve above ALREADY returned — free, no lookup. Only when it is empty and the company is plausibly venture-backed, fall back to the live crunchbase/search (20cr, fuzzy — verify name+domain) → crunchbase/company. Skip entirely for obviously non-venture companies. Note leadership_hires[] is unusable as an ICP criterion for SMB/startup targets — measured empty on 6 of 6 live accounts, including a 281-person one.
• Hiring probe (only if in rubric): prefer the numeric id from organizational_urn of the domain-resolve you already did → search_jobs {company: [{"type": "company", "value": "<id>"}], count: 20}. No resolve → search_companies {keywords: name, count: 5} + verify by name/industry (its urn is already the {type, value} object).
• Team-shape evidence (great for "engineering-led vs sales-led" criteria): linkedin/company/company_employee_stats (1cr, needs company URN) — absolute headcounts by function (verified: Engineering 26 / Sales 14 on a 79-person company). Don't sum its locations array (nested buckets: US ⊃ state ⊃ metro); cross-check totals against employee_count.