follow-ups
Skill17 starsChanged 3 months agoApache-2.0View on GitHub
Turn the loose ends a finished story leaves — out-of-scope notes, deferred review findings, deliberate TODOs — into tracked follow-up work items in the team's tracker, linked to the source story, after approval. Supports Jira, Linear, GitHub Issues, and Azure DevOps via adapters. Use at the end of a story, or when the user asks to track follow-ups.
7 other projects use a version of this.
Adopted by
Most recently taken up by
- SuperMailOS/plugintheir own version, first seen Oct 25, 2026
- mukewl/jobkittheir own version, first seen Oct 20, 2026
- WireCatLabs/cli-coretheir own version, first seen Oct 20, 2026
- GuiBayma/skillstheir own version, first seen Oct 17, 2026
- youdcode/open-companytheir own version, first seen Sep 21, 2026
- automatewithuday/gtm-prospecting-systemtheir own version, first seen Sep 18, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 7
- WireCatLabs/cli-core★ 2same name
- youdcode/open-company★ 2same name
- automatewithuday/gtm-prospecting-system★ 1same name
- GuiBayma/skills★ 1same name
- mukewl/jobkit★ 1same name
- SuperMailOS/plugin★ 1same name
- samsam007b/carriere-kit★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository13 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- coverage-checkSkill
- create-prSkill
- delegate-backlogSkill
- dev-kit-setupSkill
- e2e-generateSkill
- figma-fetchSkill
- fix-prSkill
- issue-fetchSkill
- issue-updateSkill
- plan-backlogSkill
- plan-definitionSkill
- pr-reviewSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 23
Never invent follow-ups: If there are none, say so and stop — don't pad a backlog to look thorough.
- Distinctive: line 28
Type: default Task; use a User Story when it's a user-facing increment (ask if unsure).
- Distinctive: line 37
Create each approved item and link it to the source story.
- Distinctive: line 43
Create the issue under the team.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Follow-ups
Close the loop: when a story finishes, the loose ends it surfaced should be tracked, not just described in the PR body. This skill turns them into real work items in the configured tracker, linked back to the source story — created only after approval. It's the tracking counterpart to the "Out of scope / follow-ups" section create-pr already writes.
Preconditions
.claude/dev-kit.jsonexists with atrackerblock (otherwise rundev-kit-setupfirst).- The adapter's backend is authenticated (MCP connector authorized, or
gh/azlogged in) — otherwise tell the user how to authenticate and stop. - The source story key (the item just delivered) is known, for linking. If unknown, ask once.
1. Gather the loose ends — only real ones
Collect follow-ups from the story just finished, from where they were already surfaced:
- the "Out of scope / follow-ups" list in the
create-prPR body, - deferred review findings from
fix-pr/pr-review(the "defer to a tracked issue" bucket), - deliberate TODOs / known gaps the implementation left.
Never invent follow-ups. If there are none, say so and stop — don't pad a backlog to look thorough.
2. Propose — WAIT FOR APPROVAL
For each loose end, propose a work item:
- Type: default Task; use a User Story when it's a user-facing increment (ask if unsure).
- Title + a one-line description + why (the context from the story that produced it).
- Link to the source story (and its epic/parent when there is one) for traceability.
- A sizing hint or label when the team uses them (discover, don't assume).
Present the full list and wait for explicit approval; the user may edit or drop items. Create nothing until approved.
3. Create — via the tracker's write adapter
Create each approved item and link it to the source story. Verify writes by read-back where the CLI can silently no-op.
Jira (type: "jira") — Atlassian MCP
createJiraIssue for each item (project, type, summary, description, labels); link to the source with createIssueLink ("Relates to", or a sub-task under the story when appropriate).
Linear (type: "linear") — Linear MCP
Create the issue under the team; relate it to the source (relation or sub-issue); set labels/estimate.
GitHub Issues (type: "github") — gh
gh issue create --repo <owner/name> --title <t> --body-file - --label <type>, referencing the source in the body (Follow-up of #<n> / a task-list link). Verify by read-back (gh issue view --json labels) and apply labels via REST on a miss (classic-Projects orgs can silently no-op).
Azure DevOps (type: "azure") — az boards / MCP
az boards work-item create --type "Task|User Story" ...; link to the source with az boards work-item relation add (Related / Parent).
4. Report
List each created item with its key/URL, and record them where the story lives — add a "Follow-ups tracked: <keys>" line to the PR and/or the tracker comment so the trail is visible. On partial failure, report exactly what was created and what wasn't.
Guardrails
- Never create anything before approval.
- Only genuine loose ends from the work — no fabricated backlog.
- Always link to the source story for traceability.
- Watch for secrets/PII in the source material; don't copy them into tickets.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

