Log AI generation results into project tasks

Whenever a new completion finishes generating in Token Metrics, automatically add the generated text as a comment on the corresponding task in Streamtime.

Try:

See all Streamtime + Token Metrics integrations or talk to a human

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How Knit builds this workflow

The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.

Streamtime Explore Streamtime →

Triggers

New task created

Fires when a new task or card is created in Streamtime.

Task completed

Fires when a task in Streamtime is marked complete.

Due date approaching

Fires when a task's due date in Streamtime is coming up.

Comment added

Fires when a comment is added to a task in Streamtime.

Actions

Create task

Creates a new task in Streamtime.

Update task

Updates a task's status or assignee in Streamtime.

Add comment

Posts a comment on a task in Streamtime.

Move task

Moves a task in Streamtime to a different board or list.

Token Metrics Explore Token Metrics →

Triggers

New completion generated

Fires when Token Metrics generates a response to a prompt.

Model run failed

Fires when a request to Token Metrics errors or times out.

Fine-tune job completed

Fires when a fine-tuning job in Token Metrics finishes.

Actions

Generate a completion

Sends a prompt to Token Metrics and returns the model's response.

Summarize text

Uses Token Metrics to summarize a block of text.

Classify or extract data

Uses Token Metrics to classify or extract structured data from text.

Automatically analyze and tag new project tasks When a new task is created in Streamtime, send its details to Token Metrics to automatically classify the project scope and extract key priorities. See details

Generate executive summaries from task commentary When a new comment is added to a task in Streamtime, send the text to Token Metrics to summarize the discussion for quick decision-making. See details

See all Streamtime + Token Metrics integrations → · Browse the full workflow library →

Enterprise-grade security

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FAQ

Common questions

Can Knit build “Log AI generation results into project tasks” between Streamtime and Token Metrics?

Yes — describe it in the box above and Knit's Integrations Agent researches Streamtime and Token Metrics's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.

How long does it take to build?

Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.

What's the most common AI Models + Project Management automation?

Having Token Metrics summarize sprint or board status from Streamtime for a stakeholder update, or draft a task description from a short prompt.

Can this suggest task priority or assignee automatically?

Yes — Token Metrics can read existing workload and task data from Streamtime to suggest a priority or assignee, which a human can accept or override.