Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hamzaPixl/pixl-ai --skill sprint-planninggit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hamzapixl/pixl-ai/sprint-planning)<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/sprint-planning"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/sprint-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/sprint-planning"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/sprint-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.01448 |
| Opus 5.5 | $0.00023 | $0.00579 |
| Sonnet 5.5 | $0.00012 | $0.00290 |
| Haiku 4.5 | $0.00006 | $0.00145 |
Grade A, and why
sprint-planning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Breaks down epics into sprint-sized work packages. Integrates with /task-plan output for task sourcing, maps sprint items to git branches and PRs, and produces acceptance criteria that /spec-review can validate.
Required References
Before starting, check for:
.context/task-state.json— existing task plan from/task-planor/task-persist.context/spec/requirements.json— decomposed requirements from/spec-review.claude/memory/sessions/— past session summaries for velocity calibration
Step 1: Task Sourcing
If /task-plan output exists (.context/task-state.json):
- Load the existing task breakdown — do NOT re-decompose from scratch
- Use task IDs, sizes, dependencies, and acceptance criteria as-is
- Group tasks into sprint-sized batches based on dependency chains
- Flag any tasks missing size estimates or acceptance criteria
If no task plan exists:
- Analyze the epic's scope and requirements
- Identify vertical slices (each delivering user-visible value)
- Break slices into implementable tasks
- Estimate each task (S=1pt, M=2pt, L=3pt, XL=5pt)
- Map dependencies between tasks
- Suggest running
/task-planfirst for a more detailed breakdown
Step 2: Velocity Calibration
- Check past sessions: Scan
.claude/memory/sessions/for completed sprint data - Calculate historical velocity: If past data exists, use actual points completed per sprint
- Default velocity: If no history, use conservative estimates:
- Solo agent: 8-12 points per sprint
- Multi-agent (orchestrated): 20-30 points per sprint
- Adjust for unknowns: Reduce velocity by 20% for greenfield work, new tech stacks, or unclear requirements
Step 3: Sprint Assignment
- Assign tasks to sprints respecting:
- Dependency ordering (blocked tasks go to later sprints)
- Capacity limits per sprint (based on calibrated velocity)
- Agent skill matching (frontend tasks to frontend-engineer, etc.)
- Each sprint must deliver a coherent, testable increment
- Front-load risky or uncertain work into Sprint 1
- Include a 20% buffer in each sprint for unplanned work and integration issues
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 128 lines · 58 tokens per session scan A 898f5941db69
sprint-planning is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 6mo ago), licensed MIT. It adds 58 tokens to every session and 1,448 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
story-readiness
Checks whether a story is ready to implement: clear acceptance criteria, no open questions, valid ADR and dependencies. Use when the user asks if a story, or the sprint's stories, are ready to start or build.
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
qa-project-bootstrap
Onboard a new QA engineer to an existing codebase, or audit an existing test architecture. Produces a 30-day ramp plan: codebase orientation, framework walkthrough, test architecture audit, mentorship pairing, and first-test guidance. Use when: "QA onboarding," "new tester," "ramp up," "test architecture audit,"…
remove
Remove a deployed framework or addon from the current workspace.