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/Azure-Samples/mcp-agent-langchainjsWrote 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/commands/azure-samples/mcp-agent-langchainjs/fix-lint-issues)<a href="https://agentmods.dev/commands/azure-samples/mcp-agent-langchainjs/fix-lint-issues"><img src="https://agentmods.dev/badge/commands/azure-samples/mcp-agent-langchainjs/fix-lint-issues/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/commands/azure-samples/mcp-agent-langchainjs/fix-lint-issues"><img src="https://agentmods.dev/badge/commands/azure-samples/mcp-agent-langchainjs/fix-lint-issues.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 | $0.00000 | $0.00135 |
| Opus 5.5 | $0.00000 | $0.00054 |
| Sonnet 5.5 | $0.00000 | $0.00027 |
| Haiku 4.5 | $0.00000 | $0.00014 |
Grade A, and why
fix-lint-issues 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 today.
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
Role
You're a senior expert software engineer with extensive experience in maintaining projects over long time and ensuring clean code and best practices.
Task
- Run the command
npm run lint:fixto check for lint issues while fixing the obvious ones. - Check the remaning issues and fix them, one by one.
- If you have a doubt if a specific issue should be fixed or not, ask the user. Sometimes, it's better to add an exception to the linter than to fix the issue if it doesn't make sense. ALWAYS ask the user before making such decisions.
- Continue until all issues are fixed or the user decides to stop.
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.
- today First seen · 11 lines · 0 tokens per session scan A b2189ad5ab66
fix-lint-issues is a command published in the GitHub repository Azure-Samples/mcp-agent-langchainjs (204 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 135 tokens. 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 2026-10-29.
Other commands, from other repositories
review-and-refactor
You're a senior expert software engineer with extensive experience in maintaining projects over long time and ensuring clean code and best practices.
delegate-review
Run OCR in delegation mode — OCR handles file selection and rules, the host agent performs the actual review.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
review.v1
Review code changes: /review [commit|branch|PR].
mlops
Invoke the MLOps Engineer for model serving & inference infrastructure, ML/AI pipelines, model deployment & monitoring, and infrastructure-level AI cost optimization.
aidd-churn
Rank files by hotspot score to identify prime candidates for refactoring before PR review.