sprint-planning-f439de — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited sprint-planning-f439de (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Transform raw backlog items into a structured, achievable sprint with clear goals, velocity-calibrated scope, and team-ready output.
If a professional-brain (brain/) exists, ground in it instead of re-asking for what you already know:
decisions/ (what the team agreed matters), feature entities/, and open hypotheses/ the sprint might test. Run python3 ../professional-brain/scripts/brain_query.py ./brain "<sprint goal>" and carry each fact's provenance tag through.decisions/ record, provenance-tagged. Show it, get a yes, then write with ../professional-brain/scripts/brain_write.py … --commit (append-only, dry-run by default).Once the sprint is agreed, hand it to action-runner: it previews (dry-run, risk-rated), runs only what you approve via the connected action MCP, and records what was done back to the brain. Typical: create a ticket per committed backlog item and set the sprint milestone (🟡). This skill proposes; action-runner gates and runs — never silently.
Ask for (if not already provided):
Use this structure:
"This sprint we will [deliver X outcome] so that [user/business benefit], measured by [success indicator]."
Never write sprint goals as task lists. Always outcome-first.
| Complexity | Points | Description |
|---|---|---|
| Trivial | 1 | Clearly understood, no unknowns |
| Small | 2 | Straightforward, minor effort |
| Medium | 3 | Some complexity, clear path |
| Large | 5 | Complex, needs design or research |
| Very Large | 8 | High uncertainty, may need splitting |
| Epic | 13+ | Too large — must be split before sprint |
Flag any item estimated at 8+ and recommend splitting.
Available capacity = (Team size × Sprint days × Focus hours/day) × Availability factor
Focus hours/day: 6 (accounting for meetings, Slack, admin)
Availability factor: 0.7–0.85 depending on holidays/events
Story points to commit = Historical velocity × Availability factorThis skill ships with a stdlib-only Python script that computes capacity instead of estimating it by hand. Use it whenever the team's numbers are known — it applies the availability and 80% commit-ratio rules consistently.
# Quick estimate from flags
python3 scripts/capacity_calculator.py --team 5 --days 10 --velocity 30 --availability 0.8 --carryover 5
# Detailed estimate from per-member availability (JSON via stdin or --input file.json)
echo '{"sprint_days":10,"historical_velocity":40,"carryover_points":8,
"members":[{"name":"Ada","available_days":10},{"name":"Linus","available_days":7}]}' \
| python3 scripts/capacity_calculator.py --input -The script returns available focus hours, a velocity figure adjusted for real availability, the recommended commitment (capped at 80% of velocity), and the remaining capacity for new work after carry-overs. Run it first, then build the sprint backlog to fit the recommended number. Add --json to pipe the result into other tooling.
Sprint Goal:
[Goal statement]
Team Capacity: [X] story points available (based on [Y] team members, [Z]% availability)
Sprint Backlog:
| Priority | Story | Points | Owner | Acceptance Criteria |
|---|---|---|---|---|
| 1 | [Story title] | [N] | [Team member] | [When X then Y] |
Carry-Overs from Previous Sprint:
Risks & Dependencies:
Sprint Planning Agenda:
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.