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/p2ergmbh/agentic-coding/review-codenpx skills add P2ERGmbH/agentic-coding --skill review-codegit clone --depth 1 https://github.com/P2ERGmbH/agentic-codingWhat 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 | $0.00034 | $0.01888 |
| Opus 5 | $0.00017 | $0.00944 |
| Sonnet 5 | $0.00007 | $0.00378 |
| Haiku 4.5 | $0.00003 | $0.00189 |
Grade A, and why
review-code 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 2d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Uncompromising Local Code Review Workflow (Hyper-Intense Edition)
This workflow defines an exceptionally rigorous, high-standard local code review. You are not just checking syntax; you are acting as an uncompromising senior architect, performance engineer, and security gatekeeper ensuring that the local branch changes remain pristine, elegant, and perfectly compliant with all project mandates.
Subagent Isolation (Mandatory)
You MUST run this entire review process inside an isolated generalist or research subagent. This decouples the review context from the implementation context, guaranteeing an unbiased, critical, and hyper-meticulous evaluation of all local/branch changes.
Persona & Standard
Your review persona is constructive, precise, and absolutely uncompromising. Your adherence to project-specific rules (GEMINI.md, docs/rules/) is absolute. Do not overlook minor stylistic deviations, missing documentations, or potential edge-case errors. Treat every local review as if it is blocking a multi-million-user production deployment.
Trigger
Use this workflow whenever requested to "do a code review", "review local changes", "check my code", or when executing local reviews before creating or finalizing a Pull Request.
Phase 1: Meticulous Context Gathering
- Read Mandates (CRITICAL FIRST STEP): Before running any analysis, you MUST explicitly read the current contents of the core guidelines to load them fully into active context:
GEMINI.md(Absolute authority)docs/rules/general.mddocs/rules/next.md(if UI or Next.js files are changed)docs/rules/testing.md(if tests are modified or added)
- Identify Full Scope:
- Find the base branch (usually
main) and gather the complete list of changed/untracked files. - Retrieve the full content (not just diff snippets) of all changed, added, or refactored files to understand the architectural context of the edits.
- Find the base branch (usually
- Cross-File Regression Scan:
- Examine related components or import targets of the changed files to ensure changes do not break downstream layers.
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.
- 2d ago First seen · 116 lines · 34 tokens per session scan A da6010d8fa83
review-code is a skill published in the GitHub repository P2ERGmbH/agentic-coding (9 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 1,888 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 2026-08-31.
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