Data Enrichment
Published by hubspot in agent-cli-skills
What this skill does
Match external CSV/JSONL records to CRM contacts (by email) or companies (by domain) and write enriched data back in one pass using `hubspot objects upsert`.
Add Data Enrichment to your agent
Review the source and files first. When you are ready, copy the prompt instruction or use the CLI command supported by your environment.
Install with a prompt
Paste this into a compatible coding agent:
add this skill "data-enrichment" from https://github.com/hubspot/agent-cli-skillsInstall with the CLI
Run this command in a controlled environment after reviewing the repository:
npx skills add https://github.com/hubspot/agent-cli-skills --skill data-enrichmentSkill instructions
Prereq: read bulk-operations/SKILL.md first — JSONL piping, dry-run/digest, history, and rate-limit hygiene live there. This skill is the upsert-by-natural-key workflow on top.
The core move: upsert, not search-then-create
hubspot objects upsert --type X --id-property <natural-key> reads JSONL on stdin and creates-or-updates each row in one CLI call (the CLI batches 100 rows per API request), keyed by a property (email for contacts, domain for companies). No race window, no branching. Do not loop search → empty? → create.
Per line in: {"id":"jane@example.com","properties":{"firstname":"Jane","jobtitle":"VP"}}
Per line out: {"id":"123","ok":true,"data":{...}} or {"ok":false,"error":{...}}. Order matches input. The CLI adds no fields of its own — data is the raw batch-upsert API result row.
CSV/JSONL → upsert stream
Reshape with jq, preview with --dry-run, then execute. upsert is irreversible, so the execute step re-pipes the SAME inputs plus the --digest/--confirm lifted from the preview line (upsert confirm = the row count, always). Always lowercase the natural key — CRM match is exact. Confirm available property names with hubspot properties list --type contacts; never hard-code a list. See bulk-operations/resources/json-patterns.md for reshape idioms.
# CSV → JSONL (any tool); example using csvkit
csvjson external.csv | jq -c '.[]' > external.jsonl
# Preview
cat external.jsonl \
| jq -c '{id:(.email|ascii_downcase), properties:{firstname:.first, lastname:.last, jobtitle:.title, company:.company}}' \
| hubspot objects upsert --type contacts --id-property email --dry-run \
| tee /tmp/upsert.preview.jsonl
# Lift the digest + confirm (present at every row count; upsert confirm = the row count)
digest=$(jq -r 'select(.digest != null) | .digest' /tmp/upsert.preview.jsonl)
confirm=$(jq -r 'select(.digest != null) | .target.id' /tmp/upsert.preview.jsonl)
# Execute — same pipeline, plus --digest/--confirm, capture results
cat external.jsonl \
| jq -c '{id:(.email|ascii_downcase), properties:{firstname:.first, lastname:.last, jobtitle:.title, company:.company}}' \
| hubspot objects upsert --type contacts --id-property email --digest "$digest" --confirm "$confirm" \
| tee /tmp/upsert.results.jsonl
Companies: swap --type companies --id-property domain and reshape with .domain|ascii_downcase as id.
Handle per-record OK / error output
Split with jq, inspect failure modes, retry just the failures after fixing the inputs:
jq -c 'select(.ok==true)' /tmp/upsert.results.jsonl > /tmp/upsert.ok.jsonl
jq -c 'select(.ok==false)' /tmp/upsert.results.jsonl > /tmp/upsert.failed.jsonl
jq -r '.error.status' /tmp/upsert.failed.jsonl | sort | uniq -c # status → count
The CLI does not tag rows as created-vs-updated. If the batch-upsert API result row carries a new boolean, jq -r '.data.new' /tmp/upsert.ok.jsonl | sort | uniq -c splits them; otherwise compare .data.createdAt against .data.updatedAt.
429s: split the input and rerun smaller chunks (see bulk-operations rate-limit notes). 400s usually mean a bad property name or invalid enum value — fix the reshape, rerun the failed inputs.
Destructive-op safety
upsert itself is non-destructive, but write-back can clobber populated fields. Always --dry-run first and spot-check. For bulk delete or overwrite of existing data, follow the dry-run → digest → confirm flow in bulk-operations/SKILL.md. Recovery: hubspot history --since 1h.
Match without upsert: OR-search → update
When you only want to read matches (no write-back), or the natural key isn't a CRM property, use repeated --filter flags — each flag is one OR group.
Verified cap: 5 OR groups per call. 6+ returns 400 too many filterGroups (count: N, max allowed: 5). Chunk 5 at a time:
# emails.txt: one lowercased email per line
xargs -n5 < emails.txt | while read -r e1 e2 e3 e4 e5; do
args=()
for e in "$e1" "$e2" "$e3" "$e4" "$e5"; do [ -n "$e" ] && args+=(--filter "email=$e"); done
hubspot objects search --type contacts "${args[@]}" --properties email,firstname,company
done > /tmp/matches.jsonl
jq -c '{id, properties:{lifecyclestage:"marketingqualifiedlead"}}' /tmp/matches.jsonl \
| hubspot objects update --type contacts --dry-run
For larger keyed enrichments, prefer upsert — one pipeline, no chunking math.
Files included
- SKILL.md
More skills
Parallel Data Enrichment
parallel-web/parallel-agent-skills
No summary provided.
Audit unavailable13k installsData Enrichment Integration
louisblythe/sales-skills
No summary provided.
Audit unavailable399 installsData Enrichment
merit-systems/agentcash-skills
No summary provided.
Audit unavailable138 installs

