> ## Documentation Index > Fetch the complete documentation index at: https://docs.getoneprofile.ai/llms.txt > Use this file to discover all available pages before exploring further. # Keep the rewrite and the lesson that wrote it > The agent's instructions take the lesson (its next version), and the rewrite becomes the noted contact's thread, marked Looks good, so it is what sends. Every thread of the sequence already marked Looks good keeps its words across the new version. The run stays open on the new version; threads written ahead under the old instructions that nobody read leave it, and are written again when opened. A rewrite is kept whole: slot_keys, when sent, must name every change. Repeating the call is a no-op. ## OpenAPI ````yaml /openapi.json post /sequences/{sequence_id}/agent/training/{session_id}/apply/ openapi: 3.1.0 info: contact: email: support@getoneprofile.ai name: Oneprofile Support description: >- REST API reference for Oneprofile, the GTM data layer for your CRM. Manage tables, enrichments, and integrations. Authenticate with an API key to get started. termsOfService: https://www.getoneprofile.ai/terms title: API Reference | Oneprofile version: '0.0' servers: - url: https://api.getoneprofile.ai security: [] tags: - description: >- The docked AI Assistant: its general chat about the workspace and the product, streamed as Server-Sent Events, and the one list of a person's threads across every assistant, with pin, rename, delete and the search-to-table link. name: assistant - description: >- The messages a person keeps to send the assistant again: the ones the workspace saved and the ones that ship with the product, with save, rename, edit and delete. name: assistant-prompt - description: >- Granted workspace actions: what the AI Assistant proposed or applied in a conversation, the approve and dismiss decisions on each card, the workspace's approval threshold and default grants, and the eight verbs. name: workspace-actions - description: >- The Getting started checklist: a workspace's progress through the six steps from its first people search to its first launched sequence. name: onboarding - description: Senders, connected mailboxes, tags, and the Google connect flow. name: senders - description: The workspace do-not-contact list, enforced before every send. name: suppression - description: >- The workspace's recontact rule: how long before anyone hears from us again. name: contact_cooldown - description: 'Sequence authoring: the graph, the table-backed audience, previews.' name: sequences - description: >- The outbound agent behind a sequence: the voice it writes in, its per-message prompts, what it wrote and what people told it. name: outbound-agents - description: >- The LinkedIn channel: connecting an account to a sender, its safety limits and history, and the protocol the browser extension speaks. name: linkedin - description: >- The approval queue: everything waiting on a person across every sender and channel, and the workspace's manual or automatic modes per channel. name: outreach - description: 'The unified outreach inbox: threads, replies, labels, events.' name: inbox - description: 'The AI reply layer: workspace settings, drafts, and approval.' name: inbox-ai - description: Notification rules, per-user preferences, and the Slack connection. name: notifications - description: Endpoints for seeing all available integration types. name: integration-types - description: Endpoints for creating and managing integrations. name: integrations - description: Endpoints for the generic OAuth install/claim app-listings engine. name: app-listings - description: Endpoints for creating and managing API keys. name: apikey - description: >- The Model Context Protocol endpoint: use Oneprofile from Claude Code, Claude Desktop, Cursor or any other MCP client, with an API key as the bearer token. name: mcp - description: Endpoints for managing billing and subscription information. name: billing - description: Endpoints for creating and managing tables. name: tables - description: Endpoints for table columns, formula previews, and on-demand column runs. name: table-columns - description: Endpoints for table rows and manual cell edits. name: table-rows - description: Endpoints for observing and cancelling table recompute runs. name: table-runs - description: >- Endpoints for org-shared per-column display preferences: hidden, pinned, width, and colour tint. name: table-ui-prefs - description: >- Endpoints for the org-shared names given to the column tint palette: what this organisation calls each colour. Org-level, not per-table. name: table-column-color-labels - description: >- Endpoints for the enrichment action catalog, model list, presets, draft generation, and saved agents. name: table-enrichments - description: >- Endpoints for teaching a saved agent from example rows: training sessions, per-row feedback, and the proposed prompt to approve. name: agent-training - description: >- The durable audit trail of a table's enrichment actions: configured, edited, run, cancelled, and settled cost. name: table-enrichment-audit-logs - description: Endpoints for saving and applying column templates. name: table-templates - description: Server-sent change feed for a table's grid. name: table-events - description: 'Endpoints for org-shared saved table views: sort, filters, hidden columns.' name: table-views - description: >- Endpoints for PER-USER table preferences: favourites and recently opened. Unlike the rest of the table surface these are personal, so two members of one organisation legitimately see different answers. name: table-user-prefs - description: >- Endpoints for building a table from an uploaded CSV: upload and preview the inferred columns, commit the reviewed mapping, then poll the row load. name: table-imports - description: Endpoint for downloading a table's rows as CSV. name: table-export - description: >- Endpoints for the integration a table imports from: attach and preview it, promote imported fields into columns, and run the import on demand. name: table-sources - description: >- Endpoints for a table's recurring import cadence: set it, pause it, and read the next fire times. name: table-schedules - description: >- Endpoints for pushing a table's rows out to a connected integration: list writable destinations, derive their write capabilities, and map export columns. name: table-writeback - description: >- Endpoints backing a lookup column's setup: the connections whose records a column could read, and the identity fields one record type can be looked up by. name: table-integration-lookup - description: >- Endpoints for sourcing leads from the lead database: count and preview matches, land them in a table, and keep saved searches. Alongside people and company searches, leads can be sourced from buying signals (what a company or person just did), with a catalogue endpoint behind the picker that builds them. name: find-leads - description: >- Endpoints for discovering a domain's subdomains from public certificate logs and landing the results in a table. name: find-subdomains - description: Endpoints for the credit balance meter and usage reporting. name: credits - description: >- Endpoints for the workspace referral program: the shareable link, the friends who joined through it, and claiming a code after signup. name: referral - description: >- Endpoints for the affiliate program's own dashboard: enrolling and claiming a code, the summary, stats and activity feed, the commission ledger, and identity verification and payouts. name: affiliate - description: >- Endpoints for the design partner program's customer surface: whether this workspace is a design partner, the badges its feedback has earned, and sending and reading that feedback. name: design-partner - description: >- Endpoints for the org-level AI business context (company description, ideal customer profile, buyer personas, interest signals and social proof), plus domain-based generation and the reference documents whose summaries ride alongside those fields. name: ai-context - description: >- Endpoints for the signed-in user's Google Drive connection: starting and finishing the OAuth grant, checking or dropping it, and minting the short-lived token the Google Picker needs. name: google-drive paths: /sequences/{sequence_id}/agent/training/{session_id}/apply/: post: tags: - sequences summary: Keep the rewrite and the lesson that wrote it description: >- The agent's instructions take the lesson (its next version), and the rewrite becomes the noted contact's thread, marked Looks good, so it is what sends. Every thread of the sequence already marked Looks good keeps its words across the new version. The run stays open on the new version; threads written ahead under the old instructions that nobody read leave it, and are written again when opened. A rewrite is kept whole: slot_keys, when sent, must name every change. Repeating the call is a no-op. operationId: apply_sequence_training parameters: - in: path name: sequence_id required: true schema: format: uuid title: Sequence Id type: string - in: path name: session_id required: true schema: format: uuid title: Session Id type: string requestBody: content: application/json: schema: $ref: '#/components/schemas/SequenceTrainingApplySchema' required: true responses: '200': content: application/json: schema: $ref: '#/components/schemas/SequenceTrainingReadSchema' description: Successful Response '401': content: application/json: schema: $ref: '#/components/schemas/UnauthorizedResponse' description: Unauthorized '403': content: application/json: schema: $ref: '#/components/schemas/ForbiddenResponse' description: Forbidden '404': description: Sequence, audience contact, or session not found '409': description: Sequence, agent, or training revision changed '422': description: Invalid selection, feedback, or training action '500': content: application/json: schema: $ref: '#/components/schemas/ServerErrorResponse' description: Internal server error. '502': content: application/json: schema: $ref: '#/components/schemas/ServerErrorResponse' description: Bad gateway error. '503': content: application/json: schema: $ref: '#/components/schemas/ServerErrorResponse' description: Service unavailable. security: - APIKeyHeader: [] - HTTPBearer: [] components: schemas: SequenceTrainingApplySchema: description: >- Which of the proposed changes to take, and whether to draft again with them. properties: expected_revision: minimum: 1 title: Expected Revision type: integer rewrite: default: false title: Rewrite type: boolean slot_keys: anyOf: - items: type: string maxItems: 100 type: array - type: 'null' title: Slot Keys required: - expected_revision title: SequenceTrainingApplySchema type: object SequenceTrainingReadSchema: properties: agent_id: format: uuid title: Agent Id type: string applied_version: anyOf: - type: integer - type: 'null' title: Applied Version base_version: title: Base Version type: integer contacts: items: $ref: '#/components/schemas/SequenceTrainingContactReadSchema' title: Contacts type: array created_at: format: date-time title: Created At type: string error: anyOf: - type: string - type: 'null' title: Error id: format: uuid title: Id type: string note_waiting: default: false description: >- A note was given while another contact was being written: its rewrite is worked out as soon as that write lands. title: Note Waiting type: boolean progress: $ref: '#/components/schemas/SequenceTrainingProgressSchema' proposal: anyOf: - $ref: '#/components/schemas/ContactTrainingProposal' - type: 'null' reviewed_ids: description: >- Every contact given Looks good or a note in this run, including ones that left the run to make room. items: format: uuid type: string title: Reviewed Ids type: array revision: title: Revision type: integer status: $ref: '#/components/schemas/ContactTrainingStatus' steps: items: $ref: '#/components/schemas/AiStep' title: Steps type: array required: - id - agent_id - status - revision - base_version - contacts - proposal - error - applied_version - created_at - progress title: SequenceTrainingReadSchema type: object UnauthorizedResponse: properties: detail: description: The detail of why the request is unauthorized. title: Detail type: string required: - detail title: UnauthorizedResponse type: object ForbiddenResponse: properties: detail: description: The detail of why the request is forbidden. title: Detail type: string required: - detail title: ForbiddenResponse type: object ServerErrorResponse: properties: detail: description: The detail of why the server returned an error. title: Detail type: string required: - detail title: ServerErrorResponse type: object SequenceTrainingContactReadSchema: properties: context: additionalProperties: type: string title: Context type: object fields: description: >- The contact's own columns as the run froze them, read the way the approval queue lists a contact: each fact once, a whole-record column opened into its facts. items: $ref: '#/components/schemas/SequenceTrainingContactFieldSchema' title: Fields type: array label: title: Label type: string messages: items: $ref: '#/components/schemas/SequenceTrainingMessageReadSchema' title: Messages type: array note: title: Note type: string notes: description: Every note given on this thread, oldest first. items: $ref: '#/components/schemas/SequenceTrainingNoteReadSchema' title: Notes type: array notice: anyOf: - type: string - type: 'null' description: >- The agent's answer to a note that needed no change to its instructions, in its own sentence: usually a note about this contact's own facts. title: Notice profile_mismatch: anyOf: - type: string - type: 'null' description: >- What the contact's LinkedIn profile says that their row does not, usually a job change the row has not caught up with, as one sentence: 'LinkedIn says Operations Leader at Chamber Media; the row says Sealed.' Null when they agree or no profile was read. title: Profile Mismatch record_id: format: uuid title: Record Id type: string verdict: anyOf: - $ref: '#/components/schemas/ContactReviewVerdict' - type: 'null' required: - record_id - label - context - fields - messages - verdict - note title: SequenceTrainingContactReadSchema type: object SequenceTrainingProgressSchema: description: How training on this sequence is going, counted across the run. properties: fixed: description: Lessons kept in this run. title: Fixed type: integer in_a_row: description: Contacts given Looks good, with no note, since the last note. title: In A Row type: integer lessons: description: Each lesson kept, in the agent's own sentence, oldest first. items: type: string title: Lessons type: array ready: description: Whether in_a_row has reached ready_after. title: Ready type: boolean ready_after: description: How many in a row make the agent ready to send on its own. title: Ready After type: integer reviewed: description: Contacts given Looks good or a note in this run. title: Reviewed type: integer required: - reviewed - fixed - in_a_row - ready_after - ready - lessons title: SequenceTrainingProgressSchema type: object ContactTrainingProposal: description: The session's candidate prompt update, kept pending until applied. properties: changes: items: $ref: '#/components/schemas/ContactPromptChange' title: Changes type: array made_at: default: 0 title: Made At type: integer record_id: anyOf: - format: uuid type: string - type: 'null' title: Record Id round_ids: items: format: uuid type: string title: Round Ids type: array summary: title: Summary type: string required: - summary title: ContactTrainingProposal type: object ContactTrainingStatus: description: A session's phase, also used to resume its review screen. enum: - running - reviewing - proposing - proposed - completed - abandoned title: ContactTrainingStatus type: string AiStep: additionalProperties: false description: >- One thing an AI turn did, as the wire spells it. Field-for-field identical to ``table_live_updates.TableCellActivityStepSchema`` ON PURPOSE, and the duplication is the design. That schema sits in the table stratum's kernel, which the lead search, inbox and sequence surfaces have no business importing; this one sits under every surface equally. Because the two agree exactly, the frontend's ``TimelineStep`` renders both with no conversion and no second component, which is the property worth protecting. ``test_ai_step_mirrors_the_cell_activity_step`` pins them together. Plain strings rather than enums, for the same reason the cell schema uses them: the vocabulary is open, clients must tolerate tokens they have not learned yet, and a new action should never be able to break a running dashboard. properties: action: description: >- What kind of move this was, e.g. `read_table`, `plan`, `write_column`. title: Action type: string detail: default: '' description: >- The step's input: the instruction, the column it read, the query it ran. title: Detail type: string duration_ms: anyOf: - type: integer - type: 'null' description: Wall clock for the work this step describes, never an estimate. title: Duration Ms observation: default: '' description: >- One line on what came back. The half that makes a step worth reading. maxLength: 500 title: Observation type: string outcome: default: completed description: >- `completed`, `failed`, `refused` or `stopped`. Clients must tolerate new tokens. title: Outcome type: string thought: anyOf: - type: string - type: 'null' description: >- The model's stated reasoning for choosing this step. Set by the agent loop; the assistant surfaces leave it null, and the renderer simply omits the rung. title: Thought required: - action title: AiStep type: object SequenceTrainingContactFieldSchema: properties: name: title: Name type: string value: title: Value type: string required: - name - value title: SequenceTrainingContactFieldSchema type: object SequenceTrainingMessageReadSchema: properties: authored: title: Authored type: boolean body: anyOf: - type: string - type: 'null' title: Body conditional: anyOf: - type: string - type: 'null' title: Conditional edited_body: anyOf: - type: string - type: 'null' title: Edited Body edited_subject: anyOf: - type: string - type: 'null' title: Edited Subject error: anyOf: - type: string - type: 'null' title: Error facts_used: items: type: string title: Facts Used type: array id: format: uuid title: Id type: string kind: title: Kind type: string note: title: Note type: string previous_body: anyOf: - type: string - type: 'null' title: Previous Body previous_subject: anyOf: - type: string - type: 'null' title: Previous Subject proposed_body: anyOf: - type: string - type: 'null' description: The words the rewrite waiting on this contact wrote. title: Proposed Body proposed_error: anyOf: - type: string - type: 'null' description: Why the rewrite could not write this message. title: Proposed Error proposed_send: anyOf: - $ref: '#/components/schemas/SequenceTrainingSendSchema' - type: 'null' description: The rewrite's words, read as ``send`` reads the words shown. proposed_subject: anyOf: - type: string - type: 'null' description: >- The subject the rewrite waiting on this contact wrote, when it has one: what the agent will write once the rewrite is kept. title: Proposed Subject reasoning: anyOf: - type: string - type: 'null' title: Reasoning reply_to_step_id: anyOf: - format: uuid type: string - type: 'null' description: >- The step whose thread this message replies in, or null when it opens a thread of its own. title: Reply To Step Id send: anyOf: - $ref: '#/components/schemas/SequenceTrainingSendSchema' - type: 'null' description: >- Whether the agent's words would send on their own or wait for approval, under the sequence's settings as they stand. Null for a message a person typed, one not written, or when nothing would send it (no sender, no LinkedIn account). steps: items: $ref: '#/components/schemas/AiStep' title: Steps type: array subject: anyOf: - type: string - type: 'null' title: Subject timing: title: Timing type: string title: title: Title type: string required: - id - title - timing - kind - authored - conditional - subject - body - error - note - edited_subject - edited_body - previous_subject - previous_body - reasoning - facts_used - steps - reply_to_step_id title: SequenceTrainingMessageReadSchema type: object SequenceTrainingNoteReadSchema: description: One note given on a contact's thread, and where it stands. properties: note: title: Note type: string state: $ref: '#/components/schemas/FeedbackRoundState' description: >- `pending` its rewrite is being worked out or waits to be kept; `applied` kept, so the agent learned it; `discarded` its rewrite was discarded; `settled` the agent answered that nothing needed to change, or a verdict was given instead. required: - note - state title: SequenceTrainingNoteReadSchema type: object ContactReviewVerdict: description: Only an explicit review counts as feedback. enum: - good - bad - skipped title: ContactReviewVerdict type: string ContactPromptChange: description: A coordinated change to one existing prompt slot. properties: current: title: Current type: string proposed: title: Proposed type: string rationale: title: Rationale type: string slot_key: title: Slot Key type: string required: - slot_key - current - proposed - rationale title: ContactPromptChange type: object SequenceTrainingSendSchema: description: >- Whether a message would leave on its own when its turn comes, and if not, why. properties: alone: description: >- True when the send would let these words go without a person; false when they would wait for approval in Tasks. title: Alone type: boolean doubt: anyOf: - type: string - type: 'null' description: >- When the words themselves hold the message (the agent was not confident, knew too little, or a check found something): one sentence saying what. Null otherwise. title: Doubt reason: anyOf: - $ref: '#/components/schemas/AskReason' - type: 'null' description: >- Why they would wait, in the approval queue's own reasons; null when alone. required: - alone - reason title: SequenceTrainingSendSchema type: object FeedbackRoundState: description: >- Where one note stands: being answered, learned, thrown away, or answered with no change. enum: - pending - applied - discarded - settled title: FeedbackRoundState type: string AskReason: description: >- Why a message that could have sent unattended was put in front of a person. One vocabulary for every gate between an agent writing a message and the message leaving: what the agent itself said about the draft (``LOW_CONFIDENCE``, ``FINDINGS``, ``INSUFFICIENT_DATA``, ``POLICY``), what the sender or the cadence asked for (``ALWAYS_ASK``, ``SEQUENCE_MANUAL``, ``STEP_REQUIRES_APPROVAL``), what the pacing rules refused (``DAILY_CAP``, ``CONSECUTIVE_CAP``, ``THREAD_CAP``, ``HOURLY_CAP``, ``ORG_DAILY_CAP``), what the mailbox or the thread made unsafe (``UNVERIFIED_SENDER``, ``DIFFERENT_SENDER``, ``LABEL``, ``STALE_INBOUND``, ``SEQUENCE_GONE``), and what the counterparty turned out to be (``BOT_QUESTION``, ``AUTOMATED_COUNTERPARTY``, ``AUTHENTICATION``, ``LANGUAGE``, ``LINKEDIN_ONLY``). ``KILL_SWITCH`` is the platform switch that stops unattended sending outright, and ``SEND_INTERRUPTED`` an unattended reply whose send never got as far as a provider. ``SENDER_SWITCHED_TO_MANUAL`` is a LinkedIn step queued unasked that went back to a person because its sender switched to manual before it ran. Stored on the task so the queue can say why each row is there, and so "why did nothing send" is answerable by counting rows rather than by reading logs. enum: - low_confidence - findings - insufficient_data - policy - always_ask - sequence_manual - step_requires_approval - daily_cap - unverified_sender - suppressed - different_sender - label - consecutive_cap - thread_cap - hourly_cap - org_daily_cap - stale_inbound - sequence_gone - bot_question - automated_counterparty - kill_switch - authentication - language - linkedin_only - send_interrupted - sender_switched_to_manual title: AskReason type: string securitySchemes: APIKeyHeader: in: header name: X-API-Key type: apiKey HTTPBearer: scheme: bearer type: http ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.