Install
$ agentstack add skill-yanivy9h-ai-shipr-weekly ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
You are running the AI-SHIPR Weekly Review for a product manager.
Read Settings.md first. Then read based on product_mode.
If product_mode: single (or not set):
S-Strategy/Strategic-Bets.md- All files in
I-Initiatives/ - All files in
H-Hypotheses/ - All files in
P-Proof/
If product_mode: multi:
shared/Portfolio-Roadmap.md- For each product listed under
products:in Settings.md: [product]/S-Strategy/Strategic-Bets.md- All files in
[product]/I-Initiatives/ - All files in
[product]/H-Hypotheses/ - All files in
[product]/P-Proof/ - In multi mode, label each section of the Weekly Review Report by product name.
Always read (both modes):
R-Relationships/Stakeholders/Meeting-Log.mdLearning.md
Generate the Weekly Review Report below. Be concise. This is a closing ritual, not an audit.
Weekly Review Report
Week of: [Date range]
What Moved
Initiatives or hypotheses with meaningful progress this week:
- [Item] — what changed — why it matters
Initiatives or hypotheses that did not move when they should have:
- [Item] — what was expected — what blocked it
Decisions Made
Decisions made this week (from Meeting-Log or initiative updates):
- [Decision] — rationale (if captured) — owner
Decisions surfaced but not resolved:
- [Decision] — what is blocking resolution — when it must be made
Meetings: Signal vs Noise
From Meeting-Log (if populated):
- Which meetings produced a decision or clear next action?
- Which meetings produced no actionable output?
Note: meetings with no output are a system cost. Flag if recurring.
What Was Learned
2-3 insights from the week worth persisting into Learning.md:
> Learning 1: [Specific — what happened, what it suggests] > Learning 2: [...] > Learning 3: [...] (if applicable)
These should be added to Learning.md after reviewing this output.
Setup for Next Week
Top 3 priorities for next week:
- [Priority] — why
- [Priority] — why
- [Priority] — why
Decision that must be made next week:
- [Decision] — deadline — what information is needed
One thing to stop doing or simplify:
- [Item] — reason
Loop Close Checklist
- [ ] Learning.md updated with this week's insights
- [ ] Initiative files updated with current status
- [ ] Meeting-Log reflects this week's key conversations
- [ ] Any completed experiments have an interpretation recorded
- [ ] Next week's top priorities are clear
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: yanivy9h
- Source: yanivy9h/ai-shipr
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
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Versions
- v0.1.0 Imported from the upstream source.