Clay Signals

A signal watches a set of records and emits an event when something changes in the real world — someone changes job, a company posts a role or raises a round. It has two halves, and telling them apart is the first thing to get right.

Record	Id prefix	What it is
Trigger definition	td_…	The runnable unit: name, run status, filter, output.
Signal	sig_…	The underlying watch that trigger definitions share.

id in CLI output is the trigger definition (td_…), and it is the only id these commands accept. signal.id is the other record; passing it to clay signals get is a not_found. Everything a user calls "a signal" — its name, whether it is on, what it writes to — lives on the trigger definition.

Web intent is out of scope. Read Current limitations at the bottom before telling a user something cannot be done: it lists every gap with what to do instead.

The commands

clay signals list                          # every signal in the workspace
clay signals get <triggerDefinitionId>     # one signal, with its filter, schedule, and error
clay signals create --type T --input JSON  # new signal of a supported type
clay signals update <triggerDefinitionId>  # rename, re-schedule, re-filter, change per-type settings
clay signals pause <triggerDefinitionId>   # stop signal running, and stop it spending
clay signals resume <triggerDefinitionId>  # run signal again on its existing schedule
clay signals delete <triggerDefinitionId>  # remove signal but keeping the events it captured
clay signals search-topics --query Q --entity-type person|company  # topicIds for a topic intent signal

Excluding web intent makes list rows one per signal, so they are safe to count. Narrow with jq:

clay signals list | jq -r '.data[] | "\(.id)  \(.signal.type)  \(.runStatus)"'
clay signals list | jq '[.data[] | select(.runStatus == "Errored") | .id]'

Read clay signals list --help and clay signals get --help for the exact output shapes; they are the contract.

pause and resume return the signal with runStatus already updated, so no confirming call is needed. They write nothing but the status: schedule, filter, and destination are untouched, and setting a status a signal already has changes nothing, so a retry after a network failure is safe.

Only an Active or Paused signal can be toggled. Any other runStatus — Errored, Disabled, Testing, Preview — is refused.

Pausing is the credit lever. A paused signal stops checking and stops spending — reach for it when a signal costs more than it is worth, rather than suggesting deletion.

Reach for pause before delete. Pausing already stops the signal running and stops it spending, and it is reversible. Nothing undoes a delete: recreating the signal means rebuilding it in the app and starting from a fresh baseline, so the first weeks of coverage are lost again. Confirm with the user before deleting something they may only want stopped, and show them get output first.

Identify a write target by id, not by name. get returns input — the same targeting the list row carries — so read the signal back and check what it actually watches before pausing or deleting it. Names are not unique and are not reliable selectors; see the ALL warning under Signals on audiences for the specific way name-matching goes wrong on audience signals.

Deleting keeps the data. The destination table and its rows survive, as do the signal activities already on audience entities — a delete removes the watch, not the history. It is also not idempotent: a second delete of the same id returns not_found, which here means "already gone or never existed", so do not read it as confirmation.

Creating and updating a signal

clay signals create --help is the list of creatable types and the authority on each one's --input shape. It is generated from the supported set, so it is never out of date; anything absent from it is an app job, and passing such a type says so by name rather than failing obscurely. The same goes for clay signals update --help and what that type lets you change.

Types differ in what they take. The watch — a table view, or audience segments — is common to all of them, but the settings beside it are not: one type takes search filters, another a set of topic providers. Never carry an --input shape from one type to another; read the shape for the type in hand, and prefer copying a working signal of that same type:

clay signals get td_abc123 | jq '.signal.inputs'   # copy this, edit it, feed it back

Never guess a vocabulary value — fetch it. Several --input fields take a fixed set of exactly-spelled values that a misspelling silently turns into "matches nothing": news topics, job-post seniority and employment_type, new-hire seniority levels and company size/revenue buckets. Those closed sets are enumerated in full in clay signals create --help, under each type's --input shape — read the values there rather than recalling them. The two vocabularies that page cannot enumerate: topic intent topicIds, which clay signals search-topics resolves (see Topic intent types below), and new-hire job_functions, which is resolved per workspace — prefer job_title_keywords over it.

Check for a duplicate first. Nothing stops two signals of the same type watching the same records, and each is charged in full. clay signals list and compare signal.type against input before creating another.

Resolve audience ids, never names. --input's segmentIds are ids from clay audiences list --entity-type companies|people. See the ALL warning under Signals on audiences — matching words in a segment name is how the wrong signal gets written.

A table-watching signal needs three ids, and only two have a command. clay tables list gives tableId, clay tables columns list <tableId> gives the fieldId for the identifier field. There is no command for viewId — read it off the table's URL in the app, or off input.table.viewId of an existing signal on the same table:

clay signals list | jq -r '.data[] | select(.input.table.id == "t_abc123") | .input.table.viewId'

A created signal is Paused. It neither runs nor spends until clay signals resume <id>. That order is deliberate: read it back, confirm input is what you meant, then resume. Pass --activate only when the watched set and its identifier coverage have already been checked, because a check that has run cannot be taken back.

Price the signal before choosing a cadence. Which of the two billing models a type uses decides whether cadence matters at all — see Two billing models under Common issues. For a per-record-checked type, cadence multiplies the bill and a large watched view on a fast cadence is among the most expensive things a workspace can run; narrow the watched view before slowing the cadence. Omitted, --schedule takes that type's own default, which is not the same across types — and some types accept only a subset of the cadences (topic intent checks weekly at the fastest, matching how often its providers refresh); the --type values in create --help list each type's set.

Some types are created with a default filter. Omitting --filter takes it, matching the app — job change and promotion start at confidence >= 90, which is why a new signal can look healthy and still emit less than expected. Passing --filter replaces the default rather than adding to it.

--filter and a type's own filters are two different things, and confusing them is the main way a signal ends up watching for the wrong thing.

• --filter decides which detected events fire. One flag, the same on every type, and what get returns as filter.
• filters, a key inside --input on the types that have one, is the search that decides what the signal looks for in the first place — which hires count for a new-hire signal, which postings for a job-post signal, which articles for a news signal. It lives in signal.inputs.filters.

A search filters document replaces rather than merges, and the search schemas are large and heavily defaulted: a key you leave out is set back to its default, not left as it was. So edit a real one rather than composing one from memory:

clay signals get td_abc123 | jq '.signal.inputs.filters'   # copy this, edit it, feed it back

Topic intent types have their own gate and their own vocabulary trap. PersonTopicIntent and CompanyTopicIntent are gated separately from the rest of signals, so create can fail with exit 3 on a workspace where every other type works. Their setting is providerConfigs — which intent providers to ask, and which of each provider's topics to watch — and its topicIds come from each provider's own catalog (opaque ids, except bombora's, which are the topic names spelled exactly).

Resolve topicIds with clay signals search-topics — never guess them, and never copy them off another signal. A guessed id validates and then matches nothing, and another signal's ids encode its topics, not the ones this user asked for. Describe what the user wants to detect in plain language and take the ids from the result, per provider:

clay signals search-topics --query 'sales intelligence tools' --entity-type company

Each result maps one topic to its id in every provider's catalog (matches.<provider>[].id); use each id only in a providerConfigs entry for that same provider. Pass the entity type matching the signal type — a person search excludes person-restricted topics and returns no bombora ids, because bombora is company-only.

A provider config without topicIds watches every topic that provider tracks, not none — and every topic is charged per record on every run, so an omitted topic list is a cost decision, not a blank.

Which providers a topic intent signal uses is also fixed at creation, unlike its topics: update can change the topicIds and tiers inside each config, but adding or dropping a provider is refused because each one keeps its own detection baseline. Choose the provider set deliberately at create time — changing it later means a new signal.

A failed table-watching create leaves something behind, and recovery depends on where it failed. The destination is set up before the signal is validated, and nothing cleans either up. Read the error to tell the two apart before retrying:

• The signal was rejected — an unknown view, a watched view over the monitoring limit, a rejected filter, missing permissions. No signal exists, so clay signals list shows nothing: it lists signals, not tables. Retrying makes a second destination, not a second signal. Find the leftover table first. Without --destination-table that is a new table named <Type> Events from <watched table> (<date>), which clay tables list will show; with --destination-table the table you named is now carrying a source that feeds nothing. Remove either in the app.
• The signal was created but the command still failed, on reading it back. The signal exists and runs while the command exits non-zero, so here clay signals list does show it — check there before retrying, or you end up with two signals.

An audiences signal is created in a single step and has no destination table, so neither case applies to one.

What a signal watches is fixed once created. No type lets update repoint a watched table, view, or identifier field — create a new signal and delete the old one. Name, schedule, and filter are always editable; beyond those, what update accepts is per type and narrower than what create took, so check clay signals update --help rather than assuming a field that was settable at creation still is. Run status is on neither verb; pause and resume own it.

update --input changes only the keys it names, and replaces each of them whole. Keys it leaves out are untouched, so an update changing segmentIds does not disturb filters and vice versa. segmentIds is the one key that requires an audiences signal — a table-based one cannot be given audiences to watch.

Within one key there is no merging, though: a filters document replaces the saved search outright, and any key absent from the one you send goes back to its default rather than keeping its current value. Read the current search, edit it, send it back whole.

Replacing a filter is how a signal quietly starts or stops emitting. update --filter replaces outright rather than merging, and --clear-filter removes it. Read the current one first:

clay signals get td_abc123 | jq .filter

A missing or stale identifier silently drops a record. Nothing reports it, so check coverage on the watched view or segments before trusting a new signal — see The watch column is a prerequisite under Signal types.

input is not destinationTable

The single most common misreading of this output. They are separate axes, and on a table-based signal they are two different tables.

• input — what the signal watches. Either input.table ({ id, viewId }) or input.audiences ({ segmentIds, entityType }); at most one is set, and both are null for a custom signal, which is driven by an action instead.
• destinationTable — where its events are written.

destinationTable is null for an audiences-based signal, because its output goes back onto the audience entities rather than into a table. It is also null when a table-based signal has no destination resolved, so destinationTable: null alone does not prove a signal is audience-based — check input.

Signals on audiences

An audiences-based signal writes its output back to the audience entities as signal activities. Nothing appears in a table, so don't go looking for one.

Its input.audiences.segmentIds are audience ids from clay audiences list, and entityType uses the middle spelling — ACCOUNT / CONTACT, not companies / people.

ALL in segmentIds is a sentinel, and it collides with real segment names. It means the whole audience of that entity type — not a saved segment, and not a segment called "BigQuery ALL" for example. A signal watching everything and a signal watching a segment whose name contains "ALL" are indistinguishable to a text match, so never pick a signal by matching words in a name: resolve segment ids with clay audiences list and compare segmentIds against those ids. This matters most before a write — delete on the wrong match is not recoverable.

The signal_summary default field on people and companies is derived from those signal events, so it is the record-level view of what a signal has been doing. See the audiences skill for reading it, and its filters.md for selecting records by their signal events — "companies with a job posting in the last 30 days" is an audience filter, not a signals command.

To read the captured events for one person or company, use the Audiences signals get command with --entity-id. For a saved segment, use signals get with --segment-id; to aggregate that segment by signal id and type, use signals summary. These are separate from clay signals, which manages the signal definitions and run status. The segment commands accept --signal-ids as underlying sig_… ids, not trigger definition td_… ids.

A signal that runs but produces nothing

Work down this list — the first two explain most cases, and both are visible without spending anything.

1. runStatus. Only Active and Preview run. Testing, Paused, and Disabled do not; Errored stopped after a failure.
2. filter, from get. Job change and promotion signals are created with a default of confidence >= 90, so a signal can run correctly and still emit far fewer events than the user expects. A null filter is unfiltered; a missing filter is not the same as no filter having been configured.
3. error, from get. Populated when runStatus is Errored. userFriendlyMessage is what the app shows; message is the underlying failure.
4. schedule, from get. Cadences are often weekly or monthly, so a signal may simply not have run yet. schedule.lastRunAt and the top-level lastRunAt are the truth — list deliberately omits them.
5. Where the output goes. An audiences-based signal writes activities onto entities, not rows into a table (see above).

Signal types

signal.type	Fires when	Watches by
JobChange	A tracked person's current company changes	Person LinkedIn URL
NewHire	A tracked company hires someone matching your criteria	Company identifier
Promotion	A tracked person's title advances at their current company	Person LinkedIn URL
JobPost	A tracked company opens a job posting matching your filters	Company identifier
News	A tracked company appears in news, including funding rounds	Company identifier
LinkedinPostMentions	Discontinued — a post mentioned your organization	Organization id + connection
PersonTopicIntent	A tracked person researches one of your topics	Person LinkedIn URL
CompanyTopicIntent	A tracked company researches one of your topics	Company identifier
Custom	An enrichment you configure returns a change	Any action output
WebsiteVisitorTracking	A de-anonymized visit hits your website (web intent)	Tracking script, not a record set
FakeSignal	Internal test type — not created through product flows	—

LinkedinPostMentions is no longer available: never suggest it, and do not try to create or update one — both are refused. A workspace may still hold signals of the type from before, and those are fine: they appear in list and can be read, paused, resumed, and deleted like any other. For an existing one, know that it watches an organization rather than a record set — an organizationId and a LinkedIn connection, with an optional table or audience filtering only who mentioned you — so check those three when its coverage looks wrong.

The watch column is a prerequisite, not a detail. A person-based signal tracks the LinkedIn URL on each record; a record with a missing, stale, or invalid URL is silently not monitored, and no error tells you so. Check coverage before trusting a signal — but check it in the store the signal actually watches, which input on get tells you:

• input.audiences set — the records live in Audiences, so clay audiences records search-count with a NotEmpty filter on the identifier field gives the fill rate, per the audiences skill.
• input.table set — the records live in that table, and input.table.viewId narrows the watch to one view when it is set, so coverage has to be measured over that view and not the whole table. Read /tables.

signal.inputs on get is the stored per-type configuration, returned as-is — read a working signal of a type before assuming its shape.

A user rarely names a signal type; they describe an outcome. The sections below are the prompt shapes that map to each type — recognize one, then follow Matching a request to a signal below rather than jumping straight to create.

JobChange

Use when the request is about tracked people changing employers: "tell me when any of my champions change jobs", "which of my past customers landed somewhere new", "alert me when a contact leaves their company", "track job changes across my CRM contacts". The employer is what changes — a new title at the same company is Promotion, and "who did this account hire" is NewHire.

NewHire

Use when the request is about tracked companies bringing people on: "tell me when a target account hires a VP of Sales", "which accounts just brought on a new CMO", "alert me when a company on this list hires into the persona I sell to", "find new decision-makers at my accounts". Fires when someone has actually joined; a role that is merely open is JobPost.

Promotion

Use for title advancement at the same company: "tell me when my champion gets promoted", "track title changes in my buying committee", "who in my contacts moved up to director or above", "congratulate contacts on new roles". If the company changed too, that is JobChange.

JobPost

Use for hiring as a buying trigger, while the role is open: "which of my accounts are hiring SDRs", "alert me when a target account posts a job mentioning Kubernetes", "companies hiring for the role my product serves", "use open roles to prioritize outreach".

News

Use for company news and fundraising: "tell me when my accounts raise a round", "track acquisitions in my territory", "alert me when a customer launches a product or hits the news", "use funding events to trigger outreach". Fundraising is a News topic, not a separate type.

LinkedinPostMentions

Recognize "tell me when someone mentions our company on LinkedIn", "track posts talking about our product", "who is talking about us" as brand-mention asks — and then do not reach for this type: it is no longer available (see the note above). Never suggest it, and never try to create or update one. If the workspace already has one, reading and managing it is fine; for a new brand-mention request, say plainly that no signal covers it anymore.

PersonTopicIntent

Use when the request is about which tracked people are researching something: "which of my contacts are researching data warehouses", "people in-market for our category", "prospects showing intent on the problem we solve", "who is actively looking into this space right now".

CompanyTopicIntent

Use when the request is about which tracked accounts are researching or in-market: "I want to know which of my accounts are researching or in-market for <something>", "surface accounts showing buying intent for our category", "which target accounts are in-market right now", "pull third-party intent on my account list", "prioritize accounts spiking on <topic>". Account-level intent; the same ask about named individuals is PersonTopicIntent.

Custom

Recognize "fire when <some enrichment or action output> changes" with no built-in type covering it as a Custom signal — a change watch over an arbitrary action's output. It cannot be created or updated from these commands: building or changing one is an app job, so route the user there. Existing ones read and manage normally.

WebsiteVisitorTracking

Recognize "who visited my website", "de-anonymize our site traffic", "alert me when a target account hits our pricing page" as web intent — a real signal type, but out of scope for these commands entirely: it cannot be created, updated, or even read here (see Current limitations). Route the user to the Clay app.

Matching a request to a signal

When a prompt matches one of the shapes above, work in this order — the answer is usually an existing signal's output, not a new signal:

1. Look at what already exists. clay signals list, and compare signal.type and input against what the user is asking about — resolve tables and segments by id, never by name (see Signals on audiences). A signal of the right type watching the right records already answers the question, and a second one would double the spend.
2. If a fitting signal exists, read its output rather than creating another. For a table-based signal, read destinationTable.id with the /tables skill. For an audiences-based signal, use clay audiences signals get --entity-id when one person or company is in scope, clay audiences signals get --segment-id for full event payloads across a saved segment, or signals summary for counts within a saved segment. The segment commands can filter with the underlying signal.id (sig_…) when the user means one particular signal.
3. If none fits, ask before creating. Do not create a signal the user did not ask for — propose it and get a yes. Before the create, show them exactly what will exist so they can confirm: the type, what it will watch (table + view + identifier field, or audience segments by id and name), the per-type settings (filters, providerConfigs, topics), the schedule, the event filter, and how it is charged (see Two billing models). Note that it is created Paused and only starts checking — and spending — on clay signals resume.

How signals get used

Resolve workflow trigger intent from context. The workflow CLI supports audience_signal, bound to the underlying signal.id, when signal events are the intended trigger. Compare plausible sources using the request and prior discussion, then ask if the choice remains ambiguous. See workflows/trigger-selection.md for examples and binding details.

The standard GTM shape is detect → qualify → act, and a signal is only the first step. When helping a user design one, ask what the other two are.

• Champion tracking — a JobChange signal on an audience of customer contacts (champions). An event means a warm relationship just landed at a new account: the play is enrich the new company, check ICP fit, alert the owner or open a CRM opportunity. The qualification step matters — a board seat or advisory role added alongside an existing job is not a "champion moved".
• Signal-based plays on audiences — the app pairs a signal with a segment whose filter selects records with recent events of that type (the signal_events filter — see the audiences skill's filters.md). The segment is live: records enter as events arrive and age out with the lookback window. Use that segment for membership-based workflows or exports; use an audience_signal workflow trigger when the user wants to react to signal events.
• Hiring / funding as account intent — JobPost and News on a company audience, feeding prioritization: a company hiring for the role your product serves, or one that just raised, moves up the outreach queue.
• Topic intent — PersonTopicIntent / CompanyTopicIntent mark who is researching your category now; usually combined with fit filters rather than acted on alone.

Events land in the destination — table rows, or activities on audience entities plus the derived signal_summary field. Workflows can react through an audience_signal trigger or use a segment when membership is the intended condition.

Common issues and how to avoid them

Beyond the checklist above, these are the recurring ways signals surprise users in practice:

• Signals detect changes after monitoring starts. A change-detection signal (job change, promotion) diffs fresh data against a baseline captured when monitoring began. Changes that happened before the signal existed produce no events, except for the one-time historical lookback at setup (job change defaults to 3 months, lookBackTimeWindowInMonths in signal.inputs). Set expectations accordingly: a signal created today mostly pays off in the following weeks, and "this person changed jobs last quarter, why no event?" is usually this, not a bug.
• Two billing models, and only one scales with records watched. Check which before estimating anything.
  • Per record checked — JobChange, NewHire, Promotion, JobPost, PersonTopicIntent, CompanyTopicIntent. These charge for every record examined on every run whether or not it produces an event, so a large watched set at a fast cadence is one of the most expensive things a workspace can run. Size it as (records in the watched view or segments) × runs per month, and prefer narrowing the watched set over slowing the cadence. The two intent types multiply that by each selected provider's selected topics (providerConfigs in signal.inputs), so a quiet audience still pays in full and adding a topic is a cost change.
  • Per result — News, Custom, LinkedinPostMentions. These charge for events emitted, not records scanned, so the record × frequency formula does not apply and can be wildly wrong in either direction: a large quiet audience costs little, while a small noisy one can cost a lot. Estimate from expected event volume, and treat a loosened event filter as a cost change rather than only a coverage change.
• A signal that exhausts its credit limit stays stopped. An audience signal can carry a creditLimit, and exhausting it does not throttle the signal — the run sets its status to Paused, and nothing puts it back. The one automatic credit-cycle reactivation in the product is specific to web intent, so an ordinary audience signal stays paused until someone starts it again. Do not tell a user it will pick up next cycle: check runStatus on the signals they expect to be running, and once the limit is raised or the cycle rolls over, clay signals resume each paused one. Insufficient credits surfaces the same way — at run time, not as a validation error at setup.
• The default filter eats events silently — confidence >= 90 on job change and promotion (see the checklist). When a user reports "missing" events for changes that really happened, check the filter before the watch.
• Restrictive filters look like a broken signal, and there are two layers of them. The search in signal.inputs.filters — news topics, job title keywords, seniority, locations — decides what the signal looks for, and the filter from get decides which of what it found actually fires. A signal can be healthy and emit nothing because either layer excludes everything, so read both before concluding events are missing, and loosen one at a time so you can tell which was responsible.
• Watching a live segment means the watch list moves. An audience-based signal monitors current segment membership, so records entering the segment start being monitored (with a fresh baseline — see above) and records leaving stop. If a user needs a stable cohort watched, the segment filter needs to define one.
• Duplicate signals double the spend. Two trigger definitions can share a watch or overlap on the same records. Before creating a signal, run clay signals list and check for an existing one of the same type over the same input — and prefer pausing or deleting the redundant one over leaving both running.

Error codes

JSON on stdout, a typed error envelope on stderr. Exit codes: 0 ok, 2 validation, 3 auth, 4 rate-limit, 5 network, 6 not-found.

• 3 usually means signals are not enabled for the workspace, or the credential cannot read them — a workspace-config answer for the user, not a retry.
• 6 on get most often means a sig_… was passed where a td_… belongs.

Current limitations

Everything below is not yet, not impossible. This section shrinks as commands land — when one does, delete its entry rather than rewording it, and check whether the caveats elsewhere in this file still hold.

• Not every type can be created yet. clay signals create --help lists the ones that can; Custom and web intent are app-only for now, and create refuses them by name. This set grows, so read the help rather than a remembered list. No MCP tool covers signals either. LinkedinPostMentions is no longer available — see Signal types.
• update is narrower than create, per type. Name, schedule, and filter are always editable; everything else depends on the type, and a watched table, view, or identifier field is fixed for all of them.
• Web intent (WebsiteVisitorTracking) is out of scope entirely. list excludes it and every other command refuses it, so these commands never report on or change one at all — a web intent question is an app question.
• list cannot filter or paginate. It returns every signal in one response; narrow with jq. There is no server-side filter by type, status, or input.
• list omits the schedule, last run, filter, and error. The route behind it does not carry them, so they come from get one signal at a time — an N+1 for questions like "which signals are stale?"
• No cost, health, or test commands. The API exposes estimated signal cost, job status, and validation info, but nothing surfaces them yet: size a signal by hand (see Common issues), and diagnose from get's runStatus, error, and schedule.