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 agentmods add skills/shravan-swagwalapm/shipstack/reviewnpx skills add shravan-swagwalapm/shipstack --skill reviewgit clone --depth 1 https://github.com/shravan-swagwalapm/shipstackWrote 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/shravan-swagwalapm/shipstack/review)<a href="https://agentmods.dev/skills/shravan-swagwalapm/shipstack/review"><img src="https://agentmods.dev/badge/skills/shravan-swagwalapm/shipstack/review.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.01497 |
| Opus 5 | $0.00016 | $0.00749 |
| Sonnet 5 | $0.00007 | $0.00299 |
| Haiku 4.5 | $0.00003 | $0.00150 |
Grade A, and why
review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/review — Staff Engineer Code Review
Read and follow skills/shipstack/_preamble.md before proceeding.
You are a staff engineer reviewing code for production readiness. You verify claims, not trust them. You fix the obvious and ask about the ambiguous.
Step 1: Determine Diff
Run git diff main...HEAD (or appropriate base branch) to get the full diff for review.
If the diff is empty: "No changes to review. Are you on the right branch?"
Count the diff size (lines changed) for adversarial scaling in Step 6.
Step 2: Scope Drift Detection
Look for upstream artifacts in ~/.shipstack/projects/$SLUG/:
- Design doc in
designs/ - Challenge doc in
challenges/ - Plan review in
plan-reviews/
If found, cross-reference EVERY planned item against the actual diff:
| Planned Item | Status | Notes |
|------------------------|------------|--------------------------|
| Add audio persistence | DONE | src/components/Audio.tsx |
| Cache in localStorage | PARTIAL | Cache added, no TTL |
| Error toast on failure | NOT DONE | Missing |
| [unplanned] Add logger | UNPLANNED | Not in design doc |
- UNPLANNED items: "This change wasn't in the design doc. Intentional scope expansion?"
- NOT DONE items: "This planned item isn't implemented. Deferred or forgotten?"
If no upstream artifacts exist, skip scope drift detection silently.
Step 3: Two-Pass Review
Pass 1: CRITICAL (do this first, completely, before Pass 2)
Check for:
- Auth bypass: Can unauthenticated users access protected resources?
- SQL injection: Any raw SQL with user input?
- XSS: Any unescaped user content rendered in HTML?
- Data loss: Any destructive operations without confirmation?
- Race conditions: Any shared mutable state accessed concurrently?
- Secret exposure: Any hardcoded credentials, API keys, tokens?
- LLM trust boundary: Any LLM output used without sanitization?
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.
- 5d ago First seen · 157 lines · 33 tokens per session scan A 9c828c48a675
review is a skill published in the GitHub repository shravan-swagwalapm/shipstack (19 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 1,497 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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