Ground a Jira ticket's effort estimate and risk picture in comparable past work — what similar tickets actually involved, what bit the team before, which areas carry incident history. Produces input to the team's estimate, never a number written into Jira. Use when sizing a ticket, preparing refinement, or asking what…
Build the context brief a developer needs before starting a Jira ticket — what the ticket itself says, what organizational memory adds (the decisions, meetings, and people behind it), related past work, and what is still missing. Use before picking up a ticket whose background is thin, scattered, or assumes meetings…
Use PROACTIVELY when someone asks to get better at a practice, grow toward a role, or prepare for a new responsibility — "I want to get better at code reviews", "a plan to become a senior engineer", "how do I prepare to lead a project". Goal-shaped growth with no new territory to map — the AI is the mentor, the user…
Use PROACTIVELY when someone is joining a team, rotating onto an engagement or client, ramping into an unfamiliar system or codebase, or asks to get up to speed on one — "I'm joining the payments team", "help me get up to speed on this service", "what do I need to know about this team, project, or system?".…
Write a development program record — goals, milestones, check-in cadence — into the individual's personal memory scope as one self-contained episode a later session can pick up cold. This is the record-shaping half the mentor and onboarding-guide agents run after grounding a request in org memory — a fresh ask to grow…
Read a person's development program and its check-in history out of personal memory, report where they actually stand, and write the next check-in chained to the last one — so a fresh session reconstructs goals, milestone status, and open questions without the user re-explaining any of it. Use for check-ins, progress…
Product leadership skills for Jira backlogs — story creation and management from meeting and document sources, slice-wide dedupe and consolidation, and memory-backed prioritization with an executive summary — backed by GUTT organizational memory.
Scan a JQL-scoped slice of a Jira backlog for tickets that are really the same work: duplicate and overlap clusters with cited evidence, consolidation proposals that map source tickets to one drafted item, and stale candidates each carrying its justification. Propose-only — every close, cancel, merge, or link waits…
Rank a slice of the Jira backlog on the organization's own criteria, with each item's position justified by cited evidence — what was decided, what was promised to a client, which areas keep breaking — and close with a one-page summary for leadership. Produces a proposal to argue with, never a rank written into Jira.…
Draft Jira-ready stories from source material — a meeting transcript, a wiki page, a freeform ask — and manage the ones already filed: structured updates, splits into sibling stories, links, and refreshes of stale text. Every draft cites its source and carries testable acceptance criteria; every create and edit is…