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.
npx skills add HubSpot/agent-cli-skills --skill data-enrichmentgit clone --depth 1 https://github.com/HubSpot/agent-cli-skillsWrote 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.
[](https://agentmods.dev/skills/hubspot/agent-cli-skills/data-enrichment)<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/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<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="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.01293 |
| Opus 5.5 | $0.00016 | $0.00517 |
| Sonnet 5.5 | $0.00008 | $0.00259 |
| Haiku 4.5 | $0.00004 | $0.00129 |
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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 86 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 (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":"[email protected]","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
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.
- 1mo ago Changed · +6 lines 7b75a90a6ad2
- 2mo ago First seen · 80 lines · 40 tokens per session scan A cf66001834af
data-enrichment is a skill published in the GitHub repository HubSpot/agent-cli-skills (28 stars, last pushed 9d ago), licensed Apache-2.0. It adds 40 tokens to every session and 1,293 once invoked, about $0.0002 per session on Opus 5.5. 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.
data-enrichment compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| data-enrichmentHubSpot/agent-cli-skills | Skill | 28 | 9d ago | Apache-2.0 | A | 40 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |