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/soulcodex/agentic/code-reviewnpx skills add soulcodex/agentic --skill code-reviewgit clone --depth 1 https://github.com/soulcodex/agenticWhat 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 | $0.00080 | $0.01014 |
| Opus 5 | $0.00040 | $0.00507 |
| Sonnet 5 | $0.00016 | $0.00203 |
| Haiku 4.5 | $0.00008 | $0.00101 |
Grade A, and why
code-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 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Skill
Entry point for all code reviews. Detects context and routes to the right specialized skill.
Step 0 — Load Project Map
Check for .agentic/project-map.md:
- If present: read it. Use the layer structure, key modules, and conventions it defines as the foundation for all findings. Skip redundant filesystem exploration.
- If absent: run lightweight auto-discovery:
- Detect language from
go.mod,package.json,tsconfig.json,pyproject.toml,composer.json - List top-level directories to understand project structure
- Read the entry point file (e.g.
main.go,src/index.ts,app/main.py) for ~20 lines of context - Suggest running the
project-mapskill after this review to avoid discovery overhead next time
- Detect language from
Step 1 — Detect Language and Architecture
Language detection (inspect file extensions + manifest files):
| Signal | Language |
|---|---|
go.mod present |
Go |
tsconfig.json or package.json with TypeScript devDep |
TypeScript |
pyproject.toml or setup.py |
Python |
composer.json |
PHP |
Architecture detection (inspect directory names and import patterns):
| Signal | Architecture |
|---|---|
domain/, application/, infrastructure/, ports/ directories |
Hexagonal / Clean |
| Aggregate root classes, domain events, value objects | DDD |
command/ + query/ directories, command/query handler classes |
CQRS |
| Multiple independent services each with their own data store | Microservices |
Step 2 — Route to Specialized Skill(s)
Load and apply the appropriate skill(s):
| Detected | Skill to apply |
|---|---|
| Go | code-review-go |
| TypeScript / JavaScript | code-review-typescript |
| Python | code-review-python |
| PHP | code-review-php |
| Hexagonal / DDD / CQRS / Microservices markers | code-review-architecture (in addition to language skill) |
| Mixed or unrecognized | Apply generic checklist.md only |
Multiple skills can be active simultaneously (e.g. Go + Architecture for a Go hexagonal service).
What ships with it
1 file 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.
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 · 124 lines · 80 tokens per session scan A 8acfb24024ed
code-review is a skill published in the GitHub repository soulcodex/agentic (10 stars, last pushed 2d ago), licensed MIT. It adds 80 tokens to every session and 1,014 once invoked, about $0.0004 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.
Other skills, from other repositories
review-orchestrator
Get multiple perspectives on your work — coordinate reviews across cognitive modes.
plugin-review
Review plugin quality with tiered checks and dependency scoping. Use for PR and pre-release audits.
goal-flight
Portable Goal Flight workflow for long-running repo work: planning, dispatch, review, recovery, file-backed resume.
critical-review
Radical-honesty architectural review — questions code, methodology, design, and operational fitness.
sparc-methodology
Use when you need to structure complex development work using the 5-phase SPARC methodology (Specification, Pseudocode, Architecture, Refinement, Completion).
comprehensive-code-review
Use when performing code review on a PR, reviewing code changes before merge, or when a GitHub code review is requested or received - orchestrates parallel sub-agents for correctness and safety review.