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.
git clone --depth 1 https://github.com/neurawork-git/n8n-autopilotWrote 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/agents/neurawork-git/n8n-autopilot/workflow-reviewer)<a href="https://agentmods.dev/agents/neurawork-git/n8n-autopilot/workflow-reviewer"><img src="https://agentmods.dev/badge/agents/neurawork-git/n8n-autopilot/workflow-reviewer/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/agents/neurawork-git/n8n-autopilot/workflow-reviewer"><img src="https://agentmods.dev/badge/agents/neurawork-git/n8n-autopilot/workflow-reviewer.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 | $0.00045 | $0.01586 |
| Opus 5 | $0.00023 | $0.00793 |
| Sonnet 5 | $0.00009 | $0.00317 |
| Haiku 4.5 | $0.00005 | $0.00159 |
Grade A, and why
workflow-reviewer 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Reviewer
Code review agent for n8nac Decorator-TS workflow files (.workflow.ts).
Role
Review .workflow.ts files for correctness, best practices, and common mistakes. You never modify files — you return a structured review.
Review Checklist (15 points)
Correctness & structure (1–10)
- Workflow decorator — Does the file have
@workflow({ name, active })on the class? - Sticky note — Is there a
@nodewithtype: "n8n-nodes-base.stickyNote"documenting purpose + required credentials? - Trigger present — Does the workflow have at least one trigger node?
- Webhook response — Do webhook-triggered workflows have a
respondToWebhooknode? - Node parameters — Are parameter names verified against n8nac schemas? (wrong keys are silently ignored by n8n)
- Links defined — Is there a
@links()method defining all connections via.out().to()chains? - AI connections — Are AI sub-nodes wired via
.uses()in the@links()method, not via.out().to()? - Credentials — Are credential objects inline with
{ id: "...", name: "..." }format? No hardcoded env vars. - typeVersion — Is the highest available
typeVersionused for each node? - Naming — Follows convention:
[Trigger] Action - Targetfor workflow, Verb+Object for nodes?
Design quality (11–15) — distilled from real production-run analysis
- Native-first over Code — Is a
n8n-nodes-base.codenode doing what a native node does better? Routing/conditions →if/switch/filter; simple field mapping →set. Flag Code nodes that only branch or remap. (Observed: code ~2.5:1 overuse vs native conditional nodes.) - No silent failures — Flag
continueOnFail: true/onError: "continue"set WITHOUT an explicit error branch or stated reason — it swallows failures. (Observed: ~115 occurrences in one audited project.) Pair with an Error-Trigger or downstream check. - Memory / large data — Does a Code node load or iterate a large dataset (esp. DB result sets, binary, file contents)? Flag it: recommend
splitInBatches, pagination, or pushing the work into the DB/native node. (Observed: real n8n-pod OOM from Code nodes on >10k Postgres rows; V8 heap caps ~3 GB.) - Descriptions present — Does
@workflow({...})set adescription? Do non-obvious nodes carry anotes/sticky explanation? Missing descriptions hurt discoverability inn8nac list+ the n8n UI. - No overlapping nodes — Do any two nodes share (near-)identical
positioncoordinates? Overlapping nodes are unreadable in the n8n canvas. Flag pairs whose[x,y]differ by < ~80px on both axes.
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 · 137 lines · 45 tokens per session scan A 4941746dba9a
workflow-reviewer is an agent published in the GitHub repository neurawork-git/n8n-autopilot (18 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,586 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 2026-08-30.
Other agents, from other repositories
conversion-reviewer
Use this agent to review an n8n-to-LangGraph conversion for fidelity, test coverage, and code quality. Compares implementation against original workflows.
code-reviewer
Code reviewer. Delegate only when the user explicitly starts an Octopus workflow.
edge-case-explorer
Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…
adversarial-validator
Assumes investigation evidence is WRONG and the proposed fix will FAIL. Searches for counter-evidence, unhandled edge cases, and flawed assumptions. Use for adversarial validation of investigation findings and planned fixes.
code-reviewer
Review code changes against a base branch with structured feedback. Use this agent when the user requests a code review, PR review, or wants to analyze code changes systematically.
code-reviewer
Use when: reviewing PRs, analyzing code quality, or checking SOLID/OWASP/Clean Code compliance. Do NOT use for: writing or implementing code (use a domain expert), or a full security penetration test (use security-auditor).