
bulk-operations
Foundation patterns for the hubspot CLI — JSONL piping, batch read, pagination, dry-run/digest/confirm for destructive ops, and hubspot history for recovery. Every other skill builds on this one.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/hubspot/agent-cli-skills --skill bulk-operations- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads bulk-operations automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Resources
| File | When to use |
|---|---|
resources/json-patterns.md | Reshape patterns for turning a read into an update payload, a search into a delete list, a CSV into an upsert stream. |
Source of truth
This is the hubspot agent CLI; the hs developer CLI (@hubspot/cli) is a different tool and does not manage CRM data or workflows. hubspot <command> --help is authoritative. If anything in this file contradicts --help, trust --help and tell the user. Run hubspot objects types once at the start of a session to see what object types exist in this portal (standard + custom).
Submit Feedback
Use the hubspot feedback command to send a message to the owners of this CLI tool. Pass --source agent so it's attributed to agent traffic (it defaults to user):
hubspot feedback "batch upsert timed out on 5k rows" --source agent
This can be anything from:
- Specific bugs and hiccups you encountered
- Things you wish you knew before using the CLI
- Anything your user got confused, frustrated, or upset about
- Anything the user asked for that you couldn't do
- Any tools, capabilities, or skills you wish existed that would make future tasks easier
It takes one short line, attaches to the active HubSpot account, and doesn't block the task — send it and keep going.
Output shape
Every read command (list, search, get) emits JSONL — one JSON object per line:
{"id":"123","properties":{"email":"jane@example.com","firstname":"Jane"},"createdAt":"...","updatedAt":"...","archived":false,"url":"..."}
--properties email,firstname limits which fields the server returns under .properties. Downstream jq should use .properties.email, not .prop_email.
Write commands (create, update, upsert, delete, merge, associations create) accept JSONL on stdin and emit JSONL — one result per input line: {"id":"123","ok":true,"data":{...}} or {"id":"123","ok":false,"error":{"status":...,"message":"..."}}. Order of results matches input order — safe to join by line position.
Read in batch — never one-by-one
The CLI accepts multiple IDs natively. Never pipe IDs into xargs -I{} hubspot objects get ... — that spawns one CLI process per record.
# Positional args (small, known list)
hubspot objects get --type contacts 12345 67890 23456 --properties email,firstname
# Stdin from another command — one CLI call total
hubspot associations list --from companies:67890 --to contacts \
| jq -c '{id}' \
| hubspot objects get --type contacts --properties email,firstname,jobtitle
# Bare IDs on stdin also work
printf '12345\n67890\n23456\n' | hubspot objects get --type contacts --properties email
A single hubspot objects get reads up to ~100 IDs per call via the batch endpoint. For more, page in chunks of 100.
Bulk flow: paginate first, then reshape, then write
When operating on all records of a type (or all matches of a filter), always start with pagination-loop.sh — never run a bare list or search to "check how many there are." A bare call returns at most 100 records and you will have to re-fetch them anyway. To size the job first, use hubspot objects count --type <t> [--filter "..."], which returns the total matching count (e.g. {"object_type":"contacts","total":42}) without paging.
The canonical bulk pattern is:
- Paginate all records to a JSONL file
- Reshape with
jqinto the write payload - Pipe to the write command (
update,delete, etc.) with--dry-runfirst
Pagination
list and search return at most 100 records per call. Use resources/pagination-loop.sh to collect all pages into a single JSONL file:
bash resources/pagination-loop.sh <object_type> <output_file> [properties] [extra_flags...]
Examples:
# All contacts with specific properties
bash resources/pagination-loop.sh contacts /tmp/contacts.jsonl email,firstname,lastname
# Search with a filter (passes extra flags through to the CLI)
bash resources/pagination-loop.sh contacts /tmp/leads.jsonl email,firstname '--filter' 'lifecyclestage=lead'
# All deals, default properties
bash resources/pagination-loop.sh deals /tmp/deals.jsonl
The script pages through --after cursors automatically, prints progress to stderr, and writes JSONL to the output file. Run it as a single foreground command — do not background it or reconstruct the loop inline.
Result ordering
search returns newest-first by default — it sorts descending on whichever create-date property the object type defines (createdate for contacts, hs_createdate for activities, and so on) — so the first page holds the most recent records rather than the portal's 2017-era ones. Sort on any other sortable property with --sort <property> (hs_lastmodifieddate, amount, ...) and flip direction with --sort-dir asc. list has no sort control — use search when order matters.
associations list also paginates (--limit / --after, default limit 100): under --format json the next-page cursor is at .meta.next, null once the last page is reached. A record can have far more associated records than one page holds, so treat a present cursor as "more remain" and page with --after until it is null.
Write in batch — always pipe
Write commands accept JSONL on stdin. The transformation between a read shape and a write shape is a jq reshape:
| Write command | Required per-line shape |
|---|---|
objects create | {"properties":{"field":"value"}} |
objects update | {"id":"123","properties":{"field":"value"}} |
objects upsert | {"idProperty":"email","id":"jane@example.com","properties":{...}} (or use --id-property email once) |
objects delete | {"id":"123"} |
objects merge | {"primary":"123","secondary":"456"} |
associations create | {"from":"contacts:123","to":"companies:456"} |
Use plural object names in from/to (contacts:, not contact:).
Safe destructive workflow
Irreversible writes — objects delete, merge, update, upsert, associations delete / limits-update, and metadata deletes (workflows, segments, views, reports, schemas, pipelines, properties) — always require the two-step dry-run → digest → confirm flow, at ANY row count (one record needs it just as much as 10k). Soft writes (objects create, views create/update/replace-field, label-only properties update, segments members-add) run without a digest; their --dry-run is a plain preview.
1. Dry-run — emits ONE preview line for the whole invocation (not per record), at every size:
{"ok":true,"dry_run":true,"executed":false,"mutation_kind":"RecordMutation","command":"objects delete --type contacts","target":{"kind":"contacts_record","id":"123","name":"123"},"impact":{"records_affected":1,"note":"Delete 1 contacts record(s)","reversible":false},"portal":"123456","digest":"blast-29cfdd48b583","expires_in_seconds":300,"apply_command_hint":"hubspot objects delete --type contacts --digest blast-29cfdd48b583 --confirm '123'"}
mutation_kind is RecordMutation for ≤100 rows and BulkData above the bulk threshold — the digest is present in both cases, so never filter on mutation_kind. Confirm values by command: objects delete/update → the record ID (single) or the row count (batch of 2+); objects upsert → the row count (always); objects merge → the secondary ID (one pair) or the row count (batch); metadata deletes → the target's name (workflow/view/report/schema/pipeline), the property/option name, or the row count (batch archives, associations batch ops). Don't construct the confirm value — copy it from apply_command_hint (or .target.id / .target.name on the preview line).
2. Execute within 5 minutes (digest TTL 300s): re-pipe the SAME inputs plus --digest and --confirm:
# 1. Preview
hubspot objects search --type contacts --filter "lifecyclestage=subscriber" \
| jq -c '{id}' \
| hubspot objects delete --type contacts --dry-run \
| tee /tmp/preview.jsonl
# 2. Lift the digest + confirm value (present at EVERY row count)
digest=$(jq -r 'select(.digest != null) | .digest' /tmp/preview.jsonl)
confirm=$(jq -r 'select(.digest != null) | .target.id' /tmp/preview.jsonl)
# 3. Execute — re-pipe the SAME inputs
hubspot objects search --type contacts --filter "lifecyclestage=subscriber" \
| jq -c '{id}' \
| hubspot objects delete --type contacts --digest "$digest" --confirm "$confirm"
Executing without --digest fails with digest_required (the error's next_step names the dry-run command); a wrong confirm fails with confirm_mismatch; an expired digest with digest_expired. --force is deprecated and ignored.
Recovery via hubspot history
Every destructive op (and its dry-run) is logged locally. Check what happened in the last hour and what's reversible:
hubspot history --since 1h --format table
hubspot history --since 24h --kind BulkData # only bulk ops
hubspot history --since 7d --kind MetadataDestroy # schema deletes
history does not currently restore records — it's an audit log. If you deleted something by mistake, capture the history line and tell the user to restore via the UI.
For CRM property source history (who or what changed a property — WORKFLOW, INTEGRATION, IMPORT, CRM_UI), use hubspot objects history --type <t> --properties <p>. It flattens each property's version history into one row per change; UI-driven (CRM_UI) changes are excluded by default (--include-ui to keep them). Add --id <recordId> to read one record, or omit it to scan a page. This is separate from the local hubspot history audit log above — use it to investigate why a property changed after a bulk op.
Upsert beats search-then-create
For "create if missing, update if present" (the enrichment pattern), use upsert — one CLI call per record, no race condition:
cat external.jsonl \
| jq -c '{idProperty:"email", id:.email, properties:{firstname:.first, lastname:.last, company:.company}}' \
| hubspot objects upsert --type contacts --dry-run
# Or set idProperty once (upsert is irreversible — dry-run first, then execute):
cat external.jsonl \
| jq -c '{id:.email, properties:{firstname:.first}}' \
| hubspot objects upsert --type contacts --id-property email --dry-run \
| tee /tmp/upsert.preview.jsonl
digest=$(jq -r 'select(.digest != null) | .digest' /tmp/upsert.preview.jsonl)
confirm=$(jq -r 'select(.digest != null) | .target.id' /tmp/upsert.preview.jsonl) # upsert confirm = the row count, even for one row
cat external.jsonl \
| jq -c '{id:.email, properties:{firstname:.first}}' \
| hubspot objects upsert --type contacts --id-property email --digest "$digest" --confirm "$confirm"
Rate-limit hygiene
create, update, and upsert batch stdin into chunks of up to 100 and call the real batch/create / batch/update / batch/upsert endpoints — one API call per 100 lines, not per line. delete issues one API call per stdin line. Test with head -n 50 before piping a 50k-row file — or use hubspot imports for purpose-built bulk ingest. If the API starts 429ing, the per-line (or per-chunk) output will show {"ok":false,"error":{"status":429,...}} — split your input file and retry the failed lines.
For large CSV ingests, hubspot imports is the purpose-built path: imports start (from a CSV file + import-request JSON; supports --dry-run), imports list, imports get <id>, imports cancel <id> (irreversible — dry-run first, then --digest/--confirm with the import ID), and imports errors <id>. Run hubspot imports --help for the request shape.
Common reshapes
See resources/json-patterns.md for the full set. The two you need 90% of the time:
# Read → update payload (update is irreversible — dry-run, then re-pipe with the digest/confirm from the preview)
hubspot objects search --type contacts --filter "industry=Tech" \
| jq -c '{id, properties:{lifecyclestage:"marketingqualifiedlead"}}' \
| hubspot objects update --type contacts --dry-run \
| tee /tmp/update.preview.jsonl
digest=$(jq -r 'select(.digest != null) | .digest' /tmp/update.preview.jsonl)
confirm=$(jq -r 'select(.digest != null) | .target.id' /tmp/update.preview.jsonl) # single: record ID; batch of 2+: row count
hubspot objects search --type contacts --filter "industry=Tech" \
| jq -c '{id, properties:{lifecyclestage:"marketingqualifiedlead"}}' \
| hubspot objects update --type contacts --digest "$digest" --confirm "$confirm"
# Search → delete list (delete is irreversible — dry-run, lift, then re-pipe with --digest/--confirm)
hubspot objects search --type contacts --filter "!email" \
| jq -c '{id}' \
| hubspot objects delete --type contacts --dry-run \
| tee /tmp/delete.preview.jsonl
digest=$(jq -r 'select(.digest != null) | .digest' /tmp/delete.preview.jsonl)
confirm=$(jq -r 'select(.digest != null) | .target.id' /tmp/delete.preview.jsonl) # single: record ID; batch of 2+: row count
hubspot objects search --type contacts --filter "!email" \
| jq -c '{id}' \
| hubspot objects delete --type contacts --digest "$digest" --confirm "$confirm"
Known constraints
objects deleteworks under both user-OAuth (browser login, with the object's write scope) and a service key; a 403 means the active token is missing that write scope. The exception is the--gdprpermanent purge, which requires a service key (HUBSPOT_ACCESS_TOKEN) — the GDPR endpoint does not accept user OAuth tokens.objects update/merge/upsertalso accept either token type. Some destructive operations (e.g.associationscreate/delete/batch/labels/limits,schemas delete) remain service-key-only and are enforced server-side, soHUBSPOT_SKIP_AUTH_CHECKwill not get a user token past them.hubspot owners listreturns CRM users; there is noteamsobject. For team-level operations, group byhubspot_owner_idclient-side.hubspot segmentsprovides CRM lists (Lists API):list,get,create,update(metadata),update-filters,delete,restore, andmembers-list/members-add/members-remove.hubspot sequencesprovides read-only access to Sales Hub sequences:list --user-id <id>(paginated,--namefilter),get <id> --user-id <id>(steps + settings), andenrollments <contact_id>(a contact's enrollment history). Sequences are a product API surface (Sales Hub Professional+,automation.sequences.readscope), not a CRM object type —objects list --type sequencesdoes not work, and there is no create/update/delete/enroll.- Maintaining this section: the command surface grows — do not assume an API is absent because it was when this was written. When a new command family ships (see
CHANGELOG.md), revisit these constraints.hubspot --helpis authoritative for what exists today.
FAQ
What does the bulk-operations skill do?
Foundation patterns for the hubspot CLI — JSONL piping, batch read, pagination, dry-run/digest/confirm for destructive ops, and hubspot history for recovery. Every other skill builds on this one.
How do I install bulk-operations?
Run npx skills add https://github.com/hubspot/agent-cli-skills --skill bulk-operations in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/bulk-operations/ (personal) or .claude/skills/bulk-operations/ (project).
Which AI agents can use bulk-operations?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is bulk-operations safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains bulk-operations?
It is published by hubspot in hubspot/agent-cli-skills. It has 1,791 recorded installs.
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