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/wrannaman/agentic-engineering/reviewnpx skills add wrannaman/agentic-engineering --skill reviewgit clone --depth 1 https://github.com/wrannaman/agentic-engineeringWrote 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/wrannaman/agentic-engineering/review)<a href="https://agentmods.dev/skills/wrannaman/agentic-engineering/review"><img src="https://agentmods.dev/badge/skills/wrannaman/agentic-engineering/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 | $0.00029 | $0.02515 |
| Opus 5 | $0.00015 | $0.01257 |
| Sonnet 5 | $0.00006 | $0.00503 |
| Haiku 4.5 | $0.00003 | $0.00251 |
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 4d 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 — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Skill
You are entering the review phase. You will perform a comprehensive code review using 8 parallel review agents, each examining the code from a different perspective.
Configuration
Learnings Directory Lookup:
- First, check for project-local learnings at
<git-root>/.llm/learnings/ - If not found, fall back to
[paths.learnings_directory]from~/.agentic-eng/config.toml
This allows each project to have its own learnings while maintaining backwards compatibility.
Process
Step 1: Detect Stack Structure
Detect the active stack workflow using the git-stacks KB partition as the shared source of truth:
-
list_kb_documentsfor partitiongit-stacks -
read_kb_document_by_pathfor/index.md -
Run the dedicated-client checks from
git-stacks/index.md- If a dedicated client is detected, record
STACK_CLIENTaccordingly - If no dedicated client is detected, inspect the current branch, the plan's
PR Stacksection, and GitHub base refs to determine whether this repo is using a native git stack - If you confirm a native stack, record
STACK_CLIENT=native-git - If you cannot confirm a stack, fall back to standard single-PR review
- If a dedicated client is detected, record
-
Load the matching KB client doc before running any stack-specific command:
charcoal→read_kb_document_by_pathfor/charcoal.mdgit-town→read_kb_document_by_pathfor/git-town.mdnative-git→read_kb_document_by_pathfor/native-git.md- Use the client doc as the source of truth for stack-specific commands. Never assume
gtexists unless you detected it.
If a stack is detected:
- Parse the stack to get list of branches and their parent relationships
- Each branch in the stack is a separate PR to review
Step 1.5: Choose Review Scope (Stacked PRs Only)
If in a stack with multiple branches, ask the user:
## Stack Detected
Your stack has N PRs:
| PR | Branch | Description |
|----|--------|-------------|
| 1 | feat/part-1 | [from commits] |
| 2 | feat/part-2 | [from commits] |
| 3 | feat/part-3 | [from commits] |
How would you like to review?
1. Review all PRs (recommended) - Reviews each PR against its parent
2. Review current PR only - Reviews only the current branch
3. Review entire stack as one diff - Reviews all changes from main to HEAD
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.
- 4d ago First seen · 317 lines · 29 tokens per session scan A fc12270259d4
review is a skill published in the GitHub repository wrannaman/agentic-engineering (2 stars, last pushed 4mo ago), licensed MIT. It adds 29 tokens to every session and 2,515 once invoked, about $0.0001 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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systematic-debugging
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brainstorming
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auto-perf-optimize
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
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