Collect product feedback, usage data, runtime errors, and issue reports from configured sources. Classify and group findings with supporting evidence, then apply separate project rules for implementing fixes, requesting clarification, or closing reports.
Experimental workflow for collecting and triaging product feedback, product telemetry, runtime errors, and issue reports. Use when scanning configured signal sources and applying separate fix, reply, or close rules.
Review the instructions the agent will receive before you install.
Read .agent-factory/config.yaml and apply the optional
skill_prompts.factory-collect entry as additional project guidance. Collect
only the sources named by workflows.collect.sources. For repeated patterns
across time or sources, use factory-lookback.
empty, unavailable, and truncated distinct. A missing connector,
partial page, or failed query is not an empty source.Classify each item as a verified defect, repeated symptom, feature request, subjective feedback, duplicate, out of scope, or needing more evidence. Group related reports while retaining each source record and reporter.
Implement only when workflows.collect.implement allows the change and the
repository is in scope. Stop for configured risk conditions, unclear product
intent, or evidence that cannot be reproduced. Verify the changed behavior
with the configured checks and a representative reproduction.
| Action | Gate |
|---|---|
| Reply | When missing information blocks triage or verification, ask one targeted question only if workflows.collect.reply allows it; follow configured tone and guidance. never means no public reply. |
| Close or mark fixed | Follow workflows.collect.close and wait for its proof point. Do not imply an unverified release. |
| Publish, approve, merge, or deploy | Requires its own workflow authorization; collection does not grant it. |
When an item needs more information, keep it unresolved and retain the source
thread link and the exact question. If replies are disabled, include that
question in the report for a person to send. On later collection runs, check
whether an answer arrived. Re-triage the original report together with the
answer, then apply the implementation and verification rules again; receiving
an answer does not itself authorize a fix or external action. Use
factory-lookback to compare these follow-ups with prior reports and fixes.
Summarize coverage by source, including unavailable or truncated reads. For each item or related group, give its links, classification, evidence, disposition, checks, any external action, and the exact human decision still needed.
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Guide public skill additions and updates through file placement, catalog documentation, installation discovery, integration settings, and validation. Distinguish ordinary skills from instruction-based, app-backed, and generated skills so each receives the appropriate checks.
Monitor another AI agent’s work and independently investigate the same task. Compare the original request with actual changes and test evidence, report gaps and concrete follow-up steps, and make limited fixes when authorized.
Open Agent-Native apps beside the conversation through Dispatch MCP, a connection for app tools. Create or edit content using the current screen and selection, then read saved results back to confirm the changes.
Organize large coding tasks with Claude Fable directing lower-cost subagents. Delegate bounded research, edits, and tests, then have Fable verify evidence, resolve conflicting findings, integrate changes, and review the final result.
Organize work so an expensive AI model handles planning, judgment, and final review while cheaper helper agents perform bounded research, coding, and testing. Define ownership and verification requirements, then inspect the evidence and integrate their results centrally.
Configure a software delivery workflow that turns selected feedback and maintenance signals into verified, reviewed changes. Define information sources, schedules, working directories, and separate permissions for actions such as implementation, merging, deployment, and notifications.