forge-sprint
Skill2 starsChanged 5 months agoMITView on GitHub
Group the project's task DAG into bounded sprints and review them. Use when
In this repository46 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- forge-opencode/CLAUDE.mdCLAUDE.md
- forge-adoptSkill
- forge-arch-proSkill
- forge-archSkill
- forge-autopilotSkill
- forge-autopilot-stopSkill
- forge-build-proSkill
- forge-buildSkill
- forge-deploySkill
- forge-doctorSkill
- dreamer-runSkill
- forge-evalSkill
- forge-feedbackSkill
- flowSkill
- forge-force-advanceSkill
- graduateSkill
- health-checkSkill
- forge-initSkill
- forge-monitorSkill
- forge-orchestrateSkill
- forge-plan-proSkill
- forge-planSkill
- preflightSkill
- forge-product-proSkill
- forge-productSkill
- forge-releaseSkill
- forge-resolveSkill
- forge-resumeSkill
- forge-retroSkill
- forge-reviewSkill
- forge-rulesSkill
- forge-set-profileSkill
- skill-creatorSkill
- forge-spec-proSkill
- forge-specSkill
- forge-sprint-proSkill
- forge-srs-proSkill
- forge-srsSkill
- forge-statusSkill
- forge-trace-matrixSkill
- forge-uninstallSkill
- forge-validateSkill
- watchSkill
- watch-stopSkill
- forge-whySkill
The file
Files
forge-sprint — a sprint view over the task DAG
/forge:sprint slices the project's task DAG into bounded sprints: plan commits the
next ready tasks to a sprint file; review reports what got done vs. what carries over.
It is not a parallel tracker — it references T-IDs only, and the task DAG
(pipeline/05-plan/task-dag.md) plus implementation progress
(pipeline/06-implementation/progress.md) remain the single source of truth (F-044/045).
The selection is deterministic — scripts/sprint.py does it (no LLM); this skill invokes
it and reports the result.
When to Use
/forge:sprint plan— commit the next chunk of ready tasks tosprint-NN.md./forge:sprint review— at sprint end, summarize done vs. carried into a review file./forge:sprint list— show existing sprints and their progress.
When NOT to Use
- You just want to build a milestone end-to-end →
/forge:build --milestone N. - There is no task DAG yet → run
/forge:plan(Stage 5) first.
Steps
- Plan a sprint.
It selects the nextpython3 ${CLAUDE_PLUGIN_ROOT}/scripts/sprint.py plan --cwd . \ [--size K] [--milestone N]K(default 5) ready tasks in dependency order — carry-over first: any task committed to the previous sprint that is not yet done inprogress.mdleads the new sprint and keeps its T-ID (F-047) — then writespipeline/05-plan/sprint-NN.mdand prints the committed T-IDs to stdout. Show the user the sprint contents. If it reports "nothing to plan", everything is done — say so. - Work the sprint. Build its tasks the normal way (
/forge:build, per-task or--milestone). Mark tasks done inprogress.mdas usual — the sprint file is just a view; you do not edit it by hand. - Review at sprint end.
Defaults to the latest sprint. It writespython3 ${CLAUDE_PLUGIN_ROOT}/scripts/sprint.py review --cwd . [--sprint NN]pipeline/12-release/sprint-NN-review.md(Done / Carried / Blockers / Lessons) by cross-referencing the sprint's T-IDs againstprogress.md. Summarize: how many done, what carries over, any blockers. Carried tasks automatically lead the next/forge:sprint plan. - List anytime.
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/sprint.py list --cwd .
Notes
- Opt-in (F-048). Sprint files live under
pipeline/05-plan/andpipeline/12-release/and are created only when you run this skill. A project that never uses sprints is unaffected. - T-IDs are identity (F-047). Carry-over and review track tasks by T-ID, so a task that spans sprints keeps its history. Never renumber tasks to "fit" a sprint.
- The script writes only sprint files; it never mutates the DAG,
progress.md, or pipeline state. It degrades cleanly (exit 1 + a message) when there is no DAG.
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.

