data-enrichment

data-enrichment is a skill for Claude Code, Codex from HubSpot/agent-cli-skills. It costs 40 tokens per session (1,096 once invoked), scanned A, original, Apache-2.0.

A guide for matching outside CSV or JSONL data with HubSpot contacts or companies and writing the matched information back to the CRM. CSV and JSONL are common text formats for tabular and line-by-line data.

In plain words
What is it for?
Use it to import or update contact data by email, company data by domain, and other enriched fields in one bulk workflow.
Why use it?
It avoids unreliable search-then-create workflows that can produce duplicate records when matching data arrives at the same time. It also supports previews and uses stable identifiers such as email addresses or company domains.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/hubspot/agent-cli-skills/data-enrichment
Any agent
npx skills add HubSpot/agent-cli-skills --skill data-enrichment
Clone the repo
git clone --depth 1 https://github.com/HubSpot/agent-cli-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-enrichment

README.md
[![agentmods](https://agentmods.dev/badge/skills/hubspot/agent-cli-skills/data-enrichment.svg)](https://agentmods.dev/skills/hubspot/agent-cli-skills/data-enrichment)
Your own site
<a href="https://agentmods.dev/skills/hubspot/agent-cli-skills/data-enrichment"><img src="https://agentmods.dev/badge/skills/hubspot/agent-cli-skills/data-enrichment.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,096 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.01096
Opus 5 $0.00020 $0.00548
Sonnet 5 $0.00008 $0.00219
Haiku 4.5 $0.00004 $0.00110

Measured 6d ago against content hash cf66001834af, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

data-enrichment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

data-enrichment/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 per record, 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":"[email protected]","properties":{"firstname":"Jane","jobtitle":"VP"}} Per line out: {"id":"123","ok":true,"data":{...,"new":true|false}} or {"ok":false,"error":{...}}. Order matches input.

CSV/JSONL → upsert stream

Reshape with jq, preview with --dry-run, then execute. 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 | head

# Execute (same pipeline, drop --dry-run, 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 \
| 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
jq -r '.data.new'    /tmp/upsert.ok.jsonl     | sort | uniq -c   # created vs updated

Read the full file on GitHub · 80 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 80 lines · 40 tokens per session scan A cf66001834af

Subscribe to this mod's changes

data-enrichment is a skill published in the GitHub repository HubSpot/agent-cli-skills (23 stars, last pushed yesterday), licensed Apache-2.0. It adds 40 tokens to every session and 1,096 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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