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How to Use Donely for Channel or API deploys
Learn Donely channel or api deploys with step by step workflows, realistic examples, and verified plan notes.
Donely works well for channel or api deploys when you run it like production work: locked brief, SOURCE facts, then review before publish. Donely hosts and manages isolated AI agent instances from one dashboard (donely.ai). Catalog notes free and paid plans; verify on donely.ai. Isolate prod vs staging and log tool calls. Start at /explore/donely.
This guide focuses on channel or api deploys in detail. Related Donely articles: /blog/how-to-use-donely-for-usage-monitoring, /blog/how-to-use-donely-for-credential-rotation-practices, /blog/how-to-use-donely-for-prod-vs-staging-isolation.
When this workflow is the right job
Use channel or api deploys when the deliverable is specifically this Donely job. Switch to isolated agent instance setup when that workflow already owns the asset.
Step by step workflow
1. Brief Channel or API deploys
Write what must stay true for channel or api deploys in Donely before settings or spend.
Brief: Channel or API deploys Keep: verified SOURCE facts only Avoid: invented pricing or features Success: one reviewable output
2. Open Donely for Channel or API deploys
Use the Donely surface that owns channel or api deploys. Do not mix a neighboring workflow in the same pass.
Surface: Channel or API deploys Start: pilot with one representative input Plans: donely.ai
3. Pilot Channel or API deploys
Run a single channel or api deploys pilot. Score clarity, grounding, and whether the output is reviewable.
Pilot: Channel or API deploys [ ] SOURCE facts match [ ] Output reviewable [ ] Settings logged
4. Refine Channel or API deploys
Change one channel or api deploys dimension only. Save a template from the best run.
Refine: Channel or API deploys Change: one control only Keep: SOURCE and success criteria
Practical channel or api deploys examples
Reviewer agent
Scenario: A builder configures Channel or API deploys in Donely with focus "Reviewer agent". Objective: Define a multi-agent or agentic run for Reviewer agent with human gates. Inputs: - Goal for Reviewer agent - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Reviewer agent → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Reviewer agent with roles, gates, and a successful pilot log.
HITL gate
Scenario: A builder configures Channel or API deploys in Donely with focus "HITL gate". Objective: Define a multi-agent or agentic run for HITL gate with human gates. Inputs: - Goal for HITL gate - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for HITL gate → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for HITL gate with roles, gates, and a successful pilot log.
Tool allowlist
Scenario: A builder configures Channel or API deploys in Donely with focus "Tool allowlist". Objective: Define a multi-agent or agentic run for Tool allowlist with human gates. Inputs: - Goal for Tool allowlist - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Tool allowlist → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Tool allowlist with roles, gates, and a successful pilot log.
Sandbox sample
Scenario: A builder configures Channel or API deploys in Donely with focus "Sandbox sample". Objective: Define a multi-agent or agentic run for Sandbox sample with human gates. Inputs: - Goal for Sandbox sample - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Sandbox sample → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Sandbox sample with roles, gates, and a successful pilot log.
Retry cap
Scenario: A builder configures Channel or API deploys in Donely with focus "Retry cap". Objective: Define a multi-agent or agentic run for Retry cap with human gates. Inputs: - Goal for Retry cap - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Retry cap → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Retry cap with roles, gates, and a successful pilot log.
Role charter
Scenario: A builder configures Channel or API deploys in Donely with focus "Role charter". Objective: Define a multi-agent or agentic run for Role charter with human gates. Inputs: - Goal for Role charter - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Role charter → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Role charter with roles, gates, and a successful pilot log.
Edge-case check
Scenario: A builder configures Channel or API deploys in Donely with focus "Edge-case check". Objective: Define a multi-agent or agentic run for Edge-case check with human gates. Inputs: - Goal for Edge-case check - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Edge-case check → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Edge-case check with roles, gates, and a successful pilot log.
Decision log
Scenario: A builder configures Channel or API deploys in Donely with focus "Decision log". Objective: Define a multi-agent or agentic run for Decision log with human gates. Inputs: - Goal for Decision log - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Decision log → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Decision log with roles, gates, and a successful pilot log.
Rate limit
Scenario: A builder configures Channel or API deploys in Donely with focus "Rate limit". Objective: Define a multi-agent or agentic run for Rate limit with human gates. Inputs: - Goal for Rate limit - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Rate limit → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Rate limit with roles, gates, and a successful pilot log.
Error alert
Scenario: A builder configures Channel or API deploys in Donely with focus "Error alert". Objective: Define a multi-agent or agentic run for Error alert with human gates. Inputs: - Goal for Error alert - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Error alert → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Error alert with roles, gates, and a successful pilot log.
Stop condition
Scenario: A builder configures Channel or API deploys in Donely with focus "Stop condition". Objective: Define a multi-agent or agentic run for Stop condition with human gates. Inputs: - Goal for Stop condition - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Stop condition → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Stop condition with roles, gates, and a successful pilot log.
Shared memory note
Scenario: A builder configures Channel or API deploys in Donely with focus "Shared memory note". Objective: Define a multi-agent or agentic run for Shared memory note with human gates. Inputs: - Goal for Shared memory note - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Shared memory note → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Shared memory note with roles, gates, and a successful pilot log.
Code exec off
Scenario: A builder configures Channel or API deploys in Donely with focus "Code exec off". Objective: Define a multi-agent or agentic run for Code exec off with human gates. Inputs: - Goal for Code exec off - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Code exec off → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Code exec off with roles, gates, and a successful pilot log.
Human approve send
Scenario: A builder configures Channel or API deploys in Donely with focus "Human approve send". Objective: Define a multi-agent or agentic run for Human approve send with human gates. Inputs: - Goal for Human approve send - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Human approve send → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Human approve send with roles, gates, and a successful pilot log.
Eval rubric
Scenario: A builder configures Channel or API deploys in Donely with focus "Eval rubric". Objective: Define a multi-agent or agentic run for Eval rubric with human gates. Inputs: - Goal for Eval rubric - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Eval rubric → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Eval rubric with roles, gates, and a successful pilot log.
Multi-turn plan
Scenario: A builder configures Channel or API deploys in Donely with focus "Multi-turn plan". Objective: Define a multi-agent or agentic run for Multi-turn plan with human gates. Inputs: - Goal for Multi-turn plan - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Multi-turn plan → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Multi-turn plan with roles, gates, and a successful pilot log.
Failure branch
Scenario: A builder configures Channel or API deploys in Donely with focus "Failure branch". Objective: Define a multi-agent or agentic run for Failure branch with human gates. Inputs: - Goal for Failure branch - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Failure branch → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Failure branch with roles, gates, and a successful pilot log.
Owner per step
Scenario: A builder configures Channel or API deploys in Donely with focus "Owner per step". Objective: Define a multi-agent or agentic run for Owner per step with human gates. Inputs: - Goal for Owner per step - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Owner per step → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Owner per step with roles, gates, and a successful pilot log.
Trace export
Scenario: A builder configures Channel or API deploys in Donely with focus "Trace export". Objective: Define a multi-agent or agentic run for Trace export with human gates. Inputs: - Goal for Trace export - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Trace export → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Trace export with roles, gates, and a successful pilot log.
Pilot then scale
Scenario: A builder configures Channel or API deploys in Donely with focus "Pilot then scale". Objective: Define a multi-agent or agentic run for Pilot then scale with human gates. Inputs: - Goal for Pilot then scale - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Pilot then scale → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Pilot then scale with roles, gates, and a successful pilot log.
Coder agent
Scenario: A builder configures Channel or API deploys in Donely with focus "Coder agent". Objective: Define a multi-agent or agentic run for Coder agent with human gates. Inputs: - Goal for Coder agent - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Channel or API deploys for Coder agent → Review → Cap retries → Scale Requirements: - Stay within verified Donely capabilities; do not invent features. - Confirm live plan notes on donely.ai before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Channel or API deploys setup for Coder agent with roles, gates, and a successful pilot log.
How to improve channel or api deploys
Cut noise from channel or api deploys by removing extra adjectives while preserving SOURCE facts in Donely.
Raise quality by insisting on a single success check before debating style.
Make review easier by labeling fields that must never change.
Speed iteration by cloning the last good run and altering only one control.
Stabilize outputs by pinning settings after the pilot is approved.
Reduce rework by rejecting drafts that invent claims.
Improve handoffs by recording which control produced the best result.
Harden the workflow by testing an incomplete input before trusting defaults.
Prompting and usage guidance
Name the channel or api deploys job, audience, and success check before opening Donely.
Paste only verified facts under SOURCE so Donely cannot invent details.
Specify the deliverable shape up front.
Call out fixed details versus flexible style choices.
Ask Donely to flag unsupported claims before you accept the draft.
Limitations to respect
Check Donely plan gates for channel or api deploys on donely.ai before you promise timelines.
Keep drafts unpublished until a human confirms SOURCE facts.
Donely can be wrong. Treat channel or api deploys as provisional until review.
If documentation is silent on a claim, leave it out rather than guessing.
Practical tips for this workflow
Pilot once before batching channel or api deploys in Donely.
Keep a reusable template with variables for channel or api deploys.
Separate creative instructions from SOURCE facts.
Log settings from the best run.
Common mistakes
- Skipping the pilot run before scaling volume
- Inventing pricing, quotas, or features not on official pages
- Mixing unrelated workflows in one session
- Publishing without a human review gate
Treat channel or api deploys in Donely as a production workflow: brief, pilot, refine, then ship with review. Related reading: /blog/how-to-use-donely-for-usage-monitoring, /blog/how-to-use-donely-for-credential-rotation-practices, /blog/how-to-use-donely-for-prod-vs-staging-isolation.