Apache ShardingSphere is a database enhancement layer that makes heterogeneous databases easier to access and govern as a unified system, without replacing the underlying databases. It supports distributed database capabilities such as sharding, read-write splitting, SQL federation, encryption, masking, auditing, and traffic control for enterprise data architectures.
Borrowing it
Nothing to install: this file belongs to apache/shardingsphere. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/apache/shardingsphere/master/.codex/skills/review-pr/SKILL.mdgit clone --depth 1 https://github.com/apache/shardingsphereWrote 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/apache/shardingsphere/review-pr)<a href="https://agentmods.dev/skills/apache/shardingsphere/review-pr"><img src="https://agentmods.dev/badge/skills/apache/shardingsphere/review-pr/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/apache/shardingsphere/review-pr"><img src="https://agentmods.dev/badge/skills/apache/shardingsphere/review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00077 | $0.06978 |
| Opus 5.5 | $0.00031 | $0.02791 |
| Sonnet 5.5 | $0.00015 | $0.01396 |
| Haiku 4.5 | $0.00008 | $0.00698 |
Grade A, and why
review-pr 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 today.
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 — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review PR
Purpose and Modes
Judge the latest reviewed scope from root cause, behavior, contracts, tests, and public or user-authorized repository evidence. Select one output mode:
Formal Review Mode: return one formal result for a public PR review, authorized local-candidate review, code-readiness judgment, mergeability decision, or CI review.PR Discussion Reply Mode: return a copy-ready committer reply only when the user explicitly requests a review-thread response, author or maintainer objection reply, or challenged-finding reply. Do not add a formal verdict unless requested.
Use Formal Review Mode for every explicit code or PR review and every Formal Review required by the repository completion route.
Identify a local candidate and its local-only delta in ### Coverage; do not create a separate local-preflight result format or describe local-only work as the public PR state.
Review Focus
Review focus is independent from output mode.
| Focus | Use when | CI behavior |
|---|---|---|
Code Correctness Review |
Default review of code, tests, behavior, scope, or regression risk | Do not query, wait for, or report GitHub Actions, checks, workflow runs, or Actions logs |
Mergeability Review |
The user asks whether the PR can be merged, approved, or landed | Review code and required CI or checks |
CI Review |
The user asks about checks, Actions, logs, or CI failures | Treat CI evidence as the primary target |
Explicit user scope wins. Formal Review of a local candidate uses Code Correctness Review unless the user explicitly requests CI.
In Code Correctness Review, unreviewed CI is not an evidence gap. Runtime facts may still be required from code, official specifications, public reproductions, or local verification. If such a decisive fact is unavailable, identify that fact—not CI—as the incomplete reason.
Canonical Assessment
Resolve one review basis before discovery: the effective candidate, applicable requirements, accepted behavior and project commitments, selected review focus, and admissible evidence. Run the Review Workflow against that basis and produce one mode-independent assessment: confirmed findings consolidated by fix boundary, needs-discussion conditions, incomplete-evidence gaps, and Completion Gate state.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 1.1 KB
- references/evidence-access.md 11 KB
- references/high-risk-review.md 6.1 KB
- references/review-coordination.md 15 KB
- references/review-corrections.md 5.2 KB
- references/sql-parser-review.md 3.1 KB
- scripts/build_review_inventory.py 7.8 KB runs code
- scripts/manage_review_ledger.py 65 KB runs code
- scripts/resolve_review_scope.py 5.8 KB runs code
- tests/test_build_review_inventory.py 3.1 KB runs code
- tests/test_manage_review_ledger.py 100 KB runs code
- tests/test_resolve_review_scope.py 4.2 KB runs code
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.
- today Changed · +8 lines 308ca43dc6a7
- yesterday Changed · +11 lines f96ea8d40b52
- 5d ago Changed · +4 lines cab6377e2f1c
- 7d ago Changed · +10 lines c1086be36dbb
- 10d ago Changed · +1 lines 1c46a8d88a43
- 12d ago Changed · +4 lines 9f9056fa65a4
- 15d ago Changed · +36 lines 6a91a30f7bb0
- 17d ago Changed · +7 lines 709a7de9284c
- 1mo ago Changed · +11 lines 8ad71408fe26
- 1mo ago First seen · 274 lines · 77 tokens per session scan A bd3756814d5f
review-pr is a skill published in the GitHub repository apache/shardingsphere (20,817 stars, last pushed today), licensed Apache-2.0. It adds 77 tokens to every session and 6,978 once invoked, about $0.0003 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.
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