LLM Mart Basic
@llm-mart · Joined Jun 2026
Triages AWS CloudWatch alarms using boto3 CloudWatch.describe_alarms, CloudWatch Logs Insights queries, and AWS X-Ray trace analysis via the xray-sdk. Correlates alarm triggers with deployment events.
Triages AWS CloudWatch alarms using the CloudWatch DescribeAlarms API, GetMetricData for historical analysis, and CloudTrail LookupEvents for root cause correlation. Prioritizes alerts by blast radius and provides remediation playbooks.
Triages AWS CloudWatch alarms by correlating alarm state changes with CloudTrail events and EC2 instance health using boto3. Classifies alarms by severity, identifies root cause candidates, and updates OpsGenie alerts.
Uses AWS CloudWatch SDK (boto3) to configure anomaly detection bands on metrics via PutAnomalyDetector API. Integrates with SNS for notifications and CloudWatch Synthetics for canary-based uptime monitoring.
Investigates CloudWatch metric anomalies using the AWS SDK CloudWatch.getMetricData and Logs.filterLogEvents APIs. Correlates metric spikes with log patterns and deployment events from CodeDeploy.
Executes structured diagnostic runbooks when CloudWatch Anomaly Detection triggers alarms. Uses the AWS SDK CloudWatch client (GetMetricData, DescribeAlarms) to gather context and suggest remediations.
Creates and manages AWS CloudWatch composite alarms using the CloudWatch PutCompositeAlarm API. Builds alarm rule expressions from existing metric alarms with AND/OR/NOT logic for multi-signal alerting.
Runs CloudWatch Logs Insights queries via AWS SDK for JavaScript v3. Analyzes Lambda cold starts, API Gateway latency, and ECS container logs. Generates anomaly detection alarms with math expressions.
Builds CloudWatch Logs Insights queries and metric alarms using AWS SDK v3 (@aws-sdk/client-cloudwatch-logs, @aws-sdk/client-cloudwatch). Generates cross-account observability dashboards with CloudWatch Metrics Insights.
Analyzes AWS CloudWatch Logs using the CloudWatch Logs API and Logs Insights query syntax. Identifies error patterns, calculates error rates, and generates metric filters from log data.
Investigates anomalous patterns in AWS CloudWatch Logs using the CloudWatch Logs Insights API and CloudWatch Anomaly Detection. Correlates log spikes with deployment events via AWS CodeDeploy API.
Scans AWS CloudWatch Logs using the CloudWatch Logs Insights API and CloudWatch Anomaly Detection API. Identifies unusual error patterns, latency spikes, and log volume anomalies across log groups.
Uses AWS SDK CloudWatchClient GetMetricData and CloudWatch Logs Insights StartQueryExecution to automate incident triage. Correlates alarms via DescribeAlarms with X-Ray trace segments for root cause analysis.
Manages AWS CodePipeline stages and actions using AWS SDK for JavaScript (CodePipeline, CodeBuild, CodeDeploy APIs). Automates blue-green deployments and cross-account pipeline configurations.
Uses boto3 and the AWS IAM Access Analyzer API to enumerate all roles, policies, and users, then flags permission combinations that could allow privilege escalation to AdministratorAccess. Outputs findings mapped to MITRE ATT&CK TA0004 with remediation steps and least-privilege r
Imported from agentskillexchange/skills/skills/aws-lambda-mcp-server.
The official AWS Labs MCP server collection provides AI agents with structured access to AWS documentation, service APIs, billing data, and infrastructure metadata through the Model Context Protocol, built and maintained by AWS for secure cloud automation workflows.
Imported from agentskillexchange/skills/skills/aws-s3-mcp-server.
Orchestrates AWS data pipelines using @aws-sdk/client-s3 and @aws-sdk/client-sqs. Manages S3 object lifecycle with PutObjectCommand/GetObjectCommand, processes SQS message queues via ReceiveMessageCommand with long polling, and configures S3 event notifications to SQS for event-d
Resolves AWS SDK v3 client commands and service endpoint signatures using @aws-sdk/client-* packages. Maps IAM permission requirements to specific API calls with request/response type definitions.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
/autopilot
autopilot
Run autonomous hunt loop on a target — scope check → recon → rank surface → hunt → validate → report with configurable checkpoints. Usage: /autopilot target.com [--paranoid|--normal|--yolo]
/chain
chain
Build an exploit chain — given bug A, finds B and C to combine for higher severity and payout. Knows common chain patterns: IDOR→ATO, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth. Usage: /chain
/hunt
hunt
Active vulnerability hunting. Two-track dispatcher — asks Red Team vs WAPT, hands off to hunt-dispatch skill and sibling commands. Usage: /hunt target.com | /hunt *.target.com | /hunt targets.txt [--vuln-class X] [--source-code P] [--chrome]
/intel
intel
On-demand intelligence fetch for a target — CVEs, disclosed reports, new features. Pulls NVD/GitHub-Advisory CVEs + bundled disclosed reports + hunt memory context. Usage: /intel target.com
/memory-gc
memory-gc
Inspect or rotate the autopilot ledger JSONL files (findings.jsonl, negatives.jsonl). Caps file size and keeps N rotated backups so memory does not grow unbounded.
/pickup
pickup
Pick up a previous hunt on a target — shows hunt history and untested surface from the autopilot ledger. Usage: /pickup target.com
/recon
recon
Run full recon pipeline on a target — subdomain enum (Chaos API + subfinder), live host discovery (dnsx + httpx), URL crawl (katana + waybackurls + gau), gf pattern classification, nuclei scan. Outputs to recon/<target>/ directory. Usage: /recon target.com
/remember
remember
Optional manual note on a target or the last confirmed finding. Capture is automatic during autopilot; this is for extra context. Usage: /remember
/report
report
Write a submission-ready bug bounty report. Generates H1/Bugcrowd/Intigriti/Immunefi format with CVSS 3.1 score, proof of concept, impact statement, and remediation. Run /validate first. Usage: /report
/scope
scope
Mandatory pre-flight scope check — verify an asset is in scope BEFORE any HTTP touch. Deterministic (deny-wins, default-deny) via engine/scope.py against the engagement's scope.md. Blocks out-of-scope testing. Usage: /scope <asset> [<asset> ...]
/surface
surface
Show ranked attack surface for a target from its recon manifest + hunt memory. Deterministic backing is `cbh surface <target>` (reads recon/<target>/manifest.json); LLM layer adds ledger signal. Usage: /surface target.com
/token-scan
token-scan
Meme coin and token security scan — checks for rug pull vectors (hidden mint, honeypot, fee manipulation, LP lock bypass, authority retention, bonding curve exploits, fake renounce, sandwich amplification). Manual 8-class grep audit (with an optional automated scanner if present). Usage: /token-scan <contract_path_or_dir> [--chain solana]
/triage
triage
Quick 7-Question Gate triage on a finding before writing a report. Kills N/A submissions before they happen. Faster than /validate — for quick go/no-go decisions. Usage: /triage
/validate
validate
Validate a finding — runs 7-Question Gate + 4-gate checklist. Kills weak findings before report writing. Prevents N/A submissions that hurt validity ratio. Usage: /validate
/web3-audit
web3-audit
Smart contract security audit — runs through 10 bug class checklist (accounting desync, access control, incomplete path, off-by-one, oracle errors, ERC4626, reentrancy, flash loan, signature replay, proxy/upgrade). Applies pre-dive kill signals first. Generates Foundry PoC template for confirmed findings. Usage: /web3-audit <contract.sol>
/README
README
Crabbox is a single CLI (`crabbox`). Commands are top-level, not nested under a
/actions
Actions
`crabbox actions` prepares a leased box from your repository's own GitHub
/adapter
Adapter
See [Runtime adapter stack](../features/runtime-adapter-stack.md) for the
/admin
Admin
`crabbox admin` groups trusted operator controls for coordinator-backed leases and the cloud resources behind them. Use it to inspect every lease the broker tracks, reconcile expired leases against live cloud state, force-release or delete a backing server, print provider IAM pol
/artifacts
Artifacts
`crabbox artifacts` turns a desktop lease into durable QA evidence: it collects
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