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 skills add sjarmak/coding-agent-workflows --skill code-reviewgit clone --depth 1 https://github.com/sjarmak/coding-agent-workflowsWrote 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/sjarmak/coding-agent-workflows/code-review)<a href="https://agentmods.dev/skills/sjarmak/coding-agent-workflows/code-review"><img src="https://agentmods.dev/badge/skills/sjarmak/coding-agent-workflows/code-review/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/sjarmak/coding-agent-workflows/code-review"><img src="https://agentmods.dev/badge/skills/sjarmak/coding-agent-workflows/code-review.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00031 | $0.00728 |
| Opus 5.5 | $0.00012 | $0.00291 |
| Sonnet 5.5 | $0.00006 | $0.00146 |
| Haiku 4.5 | $0.00003 | $0.00073 |
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 16d 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.
What it actually says
Code Review
Comprehensive security and quality review of uncommitted changes:
-
Inspect the task's diff against its intended base, including staged and untracked files. For uncommitted work use
git diff HEADandgit status --short; read relevant new files explicitly. -
For risky changes, establish behavioral properties from requirements and callers, not just the implementation. Identify safety properties (what must never happen) and progress properties (what must eventually happen, under which assumptions).
Map each property to affected functions, shared state, and tests. For cancellation, retries, ownership, persistence, authorization, or shared-state transitions, attempt a violating execution. Trace across awaits, callbacks, transactions, and callers outside the diff. Prefer a deterministic regression test; use the formal-methods skill when interleavings or general logical guarantees justify modeling. Ordinary edits do not require a formal model.
- For each changed file, check for:
Security Issues (CRITICAL):
- Hardcoded credentials, API keys, tokens
- SQL injection vulnerabilities
- XSS vulnerabilities
- Missing input validation
- Insecure dependencies
- Path traversal risks
Code Quality (HIGH):
- Functions > 50 lines
- Files > 800 lines
- Nesting depth > 4 levels
- Missing error handling
- console.log statements
- TODO/FIXME comments
- Public APIs whose names and types do not express their contract
AI Slop & Erosion (HIGH) — see the anti-slop rule (rules-reference/anti-slop.md), weight toward code that extends existing modules:
- Overengineering: single-implementer interfaces, single-entry registries, factories returning a constant
- Documentation noise: narration comments, docstrings that restate the function name
- Premature optimization: caching constants, parallelism for tiny collections
- Error obscuring: success booleans / sentinel values instead of raised errors, retries swallowing failures
- Hidden behavior: silent fallbacks, auto-correction without warning
- Spec deviation: unrequested features, validation that never changes an outcome
Best Practices (MEDIUM):
- Mutation patterns (use immutable instead)
- Emoji usage in code/comments
- Missing tests for new code
- Pure logic (parsers, codecs, round-trips, arithmetic, ordering, state machines) without a property test; non-blocking
- Accessibility issues (a11y)
-
Generate report with:
- Severity: CRITICAL, HIGH, MEDIUM, LOW
- File location and line numbers
- Issue description
- Suggested fix
- Violated property and evidence: reproduced implementation defect, model-only counterexample, or untested suspicion
- Reproduction command or trace, assumptions, and remaining uncertainty
Do not present a model-only counterexample as a confirmed implementation bug. When a formal check succeeds, review the specification, reachable scenarios, abstraction boundaries, and correspondence to the code. A proof of the wrong requirement is not acceptance evidence. Distinguish confidence from impact; a severe hypothetical consequence does not establish a confirmed defect.
- Block commit for confirmed CRITICAL or HIGH findings. Report unresolved high-impact risks explicitly; do not silently approve a required property whose check failed or could not run.
Never approve code with security vulnerabilities!
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.
- 16d ago Changed · +10 lines · -6 tokens per session 8644ccabb4e1
- 1mo ago First seen · 60 lines · 37 tokens per session scan A 2311dde2a757
code-review is a skill published in the GitHub repository sjarmak/coding-agent-workflows (6 stars, last pushed 17d ago), licensed MIT. It adds 31 tokens to every session and 728 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
Agent Instruction Drift Check
Procedure for comparing an agent-facing instruction doc (AGENTS.md/CLAUDE.md-style) against the actual current code and configuration to find and flag mismatches.
karpathy-guidelines
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
improve-codebase-architecture
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
agent-watchdog
Use when asked to watch, babysit, audit, review, compare, or fix another agent's work from a Codex session ID, Claude Code session/transcript, chat/thread link, PR, branch, log, or pasted run summary. Monitor until the other agent is done or blocked, reconstruct what the user asked, independently investigate the same…
find-simplifications
Use when asked to find or plan Cherry Studio cleanup, simplification, refactoring, dead-code removal, duplicated state removal, unnecessary APIs, speculative generality, or library replacements, especially when the result should become evidence-backed proposed Agent Notes.
no-comments
Spawn Comment Sicko, fix accepted findings, and offer encodings for claimed constraints.