Watt

Materialize a confirmed audience and shape it for an ad platform — given a signal stack's expression OR a roster's entity-ID set, the platform key, the user-confirmed row ceiling, and the platform's writer-script path, pulls the audience page by deterministic page, runs the script's transform, and returns file paths and row counts — never prose, never narrated hashing. Dispatched by the audience-activate skill (the EXPORT step behind /watt:audience), only after the user's explicit scale-and-identifiers confirmation.

Read who a built audience reaches, as aggregates over a deterministic sample — given a built signal stack (expression + signals) or a pre-resolved entity-ID set, samples and aggregates it and returns a two-section structured profile (the stack's own signals; the net-new traits that define the audience by lift) — never prose, never a rendered table, never an individual record. Dispatched by the audience-analyze leaves and by audience-generate-list's lookalike play (mode B, to profile a resolved seed for its defining signals), behind /watt:audience, only at the user's go-ahead.

Resolve a supplied list of people to Watt entity IDs and hand back a chainable entity-ID set — given identifiers (emails, phones, names, addresses) inline or as an uploaded CSV, matches them with entity_resolve, dedupes, and returns a workflow:// entity-IDs URI plus the counts (identifiers submitted, entities resolved). Aggregates downstream, never PII — never enriches, never echoes a record, never exports contact data. Dispatched by the audience-analyze-list leaf (to profile a list as aggregates) and the audience-generate-list leaf (to build a matched roster from a list), both behind /watt:audience.

Find and validate signals (traits) in the Watt Signal Graph for a single committed angle — or, on the user's explicit ask, a full concept set. Returns a structured, concept-grouped candidate set with per-signal evidence and an honest count of how much more is out there — never prose, never a final deliverable. Dispatched by /watt:explore (the DEPTH step) — when the user picks one angle and wants thorough coverage of it — and by the audience skills behind /watt:audience that find or validate signals (e.g. audience-generate, audience-analyze), one angle per dispatch.

Profile a list of signals (traits) against the Watt signal scoring model — compute each signal's normalized feature vector (relevance, freshness, rarity, specificity, breadth, size, coverage) from trait_search + trait_get fields, and, given a ranking method (weights / sort_by / score_by), score · rank · truncate. Enriches the signals, runs the deterministic scripts/signal_profile.py (never hand-computes the math), and returns an explicit ordered JSON profile — never prose, never a rendered table, never an individual record. Dispatched by /watt:explore and the audience skills behind /watt:audience that score a discovered pool (e.g. audience-analyze-search, audience-generate) — illustrative, not exhaustive.

Export a built audience as a platform-ready file — confirms the platform, the scale, and the identifier types with the user, then materializes the audience and runs the deterministic writer script, returning the finished file and honest row counts. Meta, Google, and Reddit are the supported platforms. Never runs unconfirmed. Not a user command — /watt:audience is the front door. Use when an export-shaped ask arrives — "export it", "push it to Meta", "push it to Google", "push it to Reddit", the audience as a file.

Read who a supplied list of people is — take a list of people as identifiers (emails, phones, names, addresses, inline or as a CSV) to resolve, or as already-resolved entity IDs (a roster from grouping, or a pasted entity-ID set), and render the discovered half of the read (the traits that define them against the world by lift, plus segmentation). No specified-signals section — the user gave people, not signals. The list way into audience-analyze, behind /watt:audience. Aggregates only — never individual records, never an export. Not a user command. Use when the user brings a list of people and asks who they are — "profile my customer list", "what do these people have in common", "read this roster's groups".

Read who a market is, starting from a plain-English brief — discover → pivot → read. The discovery-first way into audience-analyze, behind /watt:audience; size is an output, never a target. Aggregates only — never individual records, never an export. Not a user command. Use when a read-shaped ask arrives with a brief and no signals yet — "who's in the market for X", "profile this audience", "an audience profile for my client".

Read who a built audience reaches when the signals are already in hand — a signal stack fresh from generate, an explore pool, a pasted audience record, or signals the user names — skip discovery, materialize, and render the two-section read (your signals + discovered). The signals-in-hand way into audience-analyze, behind /watt:audience. Aggregates only — never individual records, never an export. Not a user command. Use when a built audience is in session or the user supplies its signals and asks who's in it — "who's actually in this audience", "what do these people look like".

Read who a built audience reaches, as aggregates over a deterministic sample — and, on request, a shareable signal membership report. The read step behind /watt:audience; routes to the way in that fits what the user has — a brief, signals they already hold, or a list of people. Aggregates only — never individual records, never contact data, never an ad-platform export. Not a user command — /watt:audience is the front door. Use when a read-shaped ask arrives — "who's actually in this audience", "what do these people look like", "an audience profile for my client" — or to sanity-check a signal stack before exporting.

17 hooks across 5 events

Watt Signal Graph MCP. First tool call triggers OAuth in the browser.

Guided-journey voice for Watt — narrated steps, one unmistakable decision per turn, host-native inline visuals.