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 Rijul1204/rashedul-agentic-engineering --skill rijuls-reviewgit clone --depth 1 https://github.com/Rijul1204/rashedul-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/rijul1204/rashedul-agentic-engineering/rijuls-review)<a href="https://agentmods.dev/skills/rijul1204/rashedul-agentic-engineering/rijuls-review"><img src="https://agentmods.dev/badge/skills/rijul1204/rashedul-agentic-engineering/rijuls-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/rijul1204/rashedul-agentic-engineering/rijuls-review"><img src="https://agentmods.dev/badge/skills/rijul1204/rashedul-agentic-engineering/rijuls-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 | $0.00209 | $0.12878 |
| Opus 5 | $0.00105 | $0.06439 |
| Sonnet 5 | $0.00042 | $0.02576 |
| Haiku 4.5 | $0.00021 | $0.01288 |
Grade A, and why
rijuls-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 10d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rijul's Review
A four-hat adversarial review — each hat an independent agent — that ends in per-role confidence scores and ranked P0–P3 findings, reconciled by a fifth deduplicator agent into one master list. Its purpose is to catch what a single-perspective read misses and to force the reviewer to justify both low confidence (what's broken/risky) and high confidence (why it's actually solid, plus residual risk) — never a bare number. A clean pass here is necessary-not-sufficient: the four hats are the same model reading the same author's framing (correlated, not statistically independent), so an independent-model (Codex) pass remains the real merge gate — this review front-loads and cheapens that pass, it does not replace it.
Each hat's full method + output shape lives in its own references/role-*.md file (passed verbatim as that hat's sub-agent prompt); the shared severity scale, per-finding required fields, and verdict vocabulary live in references/finding-format.md. This SKILL.md is the orchestrator: the Hard Rules every hat applies, the hats table, and the five-agent execution mode. See Targeting & relationship to /code-review at the bottom for the artifact forms it accepts.
Hard rules (non-negotiable)
- A review is static inspection only unless Rijul explicitly asks for verification. Do NOT run tests, lint, format, typecheck, knip, builds, quality gates, browser smoke, database probes, dependency installation, or any other executable verification during a review. Read the diff, source, callers, tests, configs, and existing check results; reason from that evidence. You may identify a missing or inadequate test/gate as a finding, but do not execute it and do not make review completion contingent on running it. Only cross this boundary when Rijul separately and explicitly asks to test, verify, reproduce, smoke, or run gates.
- Read everything first. No file left unread. Before scoring, open every file the artifact names or depends on — the files to be modified, the files to be created (read their siblings/templates), the files referenced as "unchanged" reference points, the call sites, the test fixtures, and the immediate collaborators of each. If the artifact cites
file:line, open that file and verify the line says what's claimed. Grep to confirm "no other importers" / "only consumer" / "already does X" claims rather than trusting them. List the files you read in the output so the user can audit coverage. - Four hats, four independent scores. Score from each role separately. Do not average into one number — each hat sees different risk.
- Justify low AND high.
- < 80%: you MUST explain why — the specific gaps, unverified assumptions, missing tests, edge cases, or risks that hold the score down, and what would raise it.
- > 90%: you MUST also explain why — what concretely makes it strong (verified claims, covered edge cases, reversibility, test coverage) AND the residual risk that keeps it from 100%.
- 80–90%: explain the main reservation in one or two lines.
- Verify, don't trust. Every load-bearing claim in the artifact gets independently checked against the code. Call out any claim that turns out to be wrong, stale, or unverifiable. A confidently-worded claim that you could not verify is a confidence deduction, not a pass.
- Pyramid principle. Lead each role with the score + the one-sentence verdict, then the justification.
- Cost, not just correctness. A change that compiles, passes every test, and is logically correct can still be a defect if it is slow by construction — most often an N+1: a per-item query or
awaitinside a loop over a collection. Lint / typecheck / unit tests are structurally blind to it (an N+1 is correct, just slow), and it hides behind small local/test data, surfacing only at real volume. For any read over a collection, the reviewer MUST ask: does the query count stay constant as the collection grows, or scale with it? If it scales — a per-rowawait, an unbatched lookup, an unboundedSELECT, a filtered column with no index — that is a finding to flag, even when nothing fails. - jsdom-green ≠ browser-correct for native DOM/event semantics. A change that passes a jsdom unit test can still be wrong in a real browser whenever it leans on native behavior jsdom models loosely: event propagation across the React root, focus,
showModal()/::backdrop/inert, nativedocument/windowlisteners, layout/measurement, or UA pseudo-classes (:modal). jsdom false-passes these. So a load-bearing claim about such behavior is verified in a real browser (Chrome MCP), not accepted because a jsdom test is green — and a jsdom test asserting such behavior is itself suspect (a "spec-faithful fixture" trap; a green test proving a browser fact can be a false negative for bugs). Corollary bug class the Engineer hat MUST check whenever a native<dialog>modal is introduced: keyboard shortcuts still fire behind it.showModal()blocks POINTER input but NOT keydowns, and React's syntheticstopPropagation()does NOT reliably stop nativedocument/windowlisteners (React 18 delegates at the root container) — so every shortcut that can be live while the modal is open must stand down (guard each handler ondialog[open], e.g.isModalDialogOpen(); a dialog-boundarystopPropagationis not enough). Audit BOTH source-sets: (1) top-level global shortcuts, AND (2) shortcuts on components that stay mounted behind the modal — most-missed: an editor left mounted while a delete confirm opens over it (its Cmd+S / Cmd+K leak). The only handler you leave unguarded is one registered by the modal itself — and verify a handler's consumer scope by grep before calling it "modal-scoped," don't assume. Ordering matters: for an app-owned chord that overrides a browser-reserved key (Cmd+O / Cmd+S / Cmd+K, "/"), callpreventDefault()on the matched chord FIRST, THEN theisModalDialogOpen()early-return — a guard that returns beforepreventDefaultsuppresses the app action but lets the chord fall through to the browser's native action (Open File / Save Page / address-bar / quick-find) behind the modal. Second corollary — focus-return on close. When an overlay/dialog conditionally renders its OWN trigger (!open ? <trigger> : <overlay>), do NOT set the focus-restore target by readingdocument.activeElementinside the open-effect — by the time that effect runs the closed-state trigger has already unmounted, so it captures<body>and closing DROPS keyboard focus. The restore target must be captured synchronously (before the trigger unmounts) or be a stable ref to the remounting trigger; also latch "was ever open" so page-load doesn't steal focus, and suppress the refocus on a route-change close (navigation shouldn't yank focus back to the trigger). jsdom implementsfocus()/activeElementenough to pin the ref wiring in a test, but the visible focus ring + route-change-close behavior are a real-browser check. Third corollary — custom (non-native) modals are invisible to adialog[open]guard. A shortcut guard that queries onlydialog[open](nativeshowModal()dialogs) does NOT see a customrole="dialog"/aria-modaloverlay (a portaled<div>), so every global shortcut (Cmd+O go-to-file, "/", Cmd+S, tree-nav) still fires BEHIND it. When a change introduces a custom modal overlay, it MUST opt into the guard (e.g. adata-app-modalmarker the guard also queries) — AND any shortcut that is the overlay's OWN control (the chord that toggles/closes it) must use a native-only probe, or it stands down against its own overlay and can no longer close it.
What ships with it
7 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.
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.
- 10d ago First seen · 180 lines · 209 tokens per session scan A 4e3ba2749d67
rijuls-review is a skill published in the GitHub repository Rijul1204/rashedul-agentic-engineering (2 stars, last pushed 1mo ago), licensed MIT. It adds 209 tokens to every session and 12,878 once invoked, about $0.0010 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
refactor
Guides a refactor, cleanup, or restructure with the right decomposition. Use when the user asks to refactor, simplify, extract, or modernize code.
pre-publish-review
Nuclear-grade 12-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (orchestrator manual QA plus one gate reviewer) for holistic review, and 1 oracle for overall release…
work-with-pr
Full PR lifecycle in a fresh task-owned git worktree: implement via the ulw-loop skill with mandatory evidence-bound manual QA → reviewer-readable English PR → verification loop (CI + Cubic, where Cubic is skipped only when its quota is exhausted) → merge by default → worktree cleanup. Decomposes one task into the…
remove-ai-slops
Removes AI-generated code smells from branch changes or an explicit file list behind regression tests. Use when the user asks to clean up, deslop, or remove AI-slop patterns from recent changes.
review-work
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed work.
tech-debt-audit
Thorough, file-cited technical debt audit across 9 dimensions using AST-grep (tree-sitter), grep, LSP, and language-native tooling. Produces TECHDEBTAUDIT.md with severity, effort estimates, and prioritized fixes. Use when asked for codebase health check, tech debt audit, architecture review, code quality assessment…