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run-tasks
kbrdn1
Execute GitHub issues or task files with full EPCT workflow and PR creation
prompt-command
kbrdn1
Create and optimize command prompts with command-specific patterns
prompt-agent
kbrdn1
Create and optimize agent prompts with agent-specific patterns
premortem
kbrdn1
"Exécute un premortem sur n'importe quel plan, lancement, produit, recrutement, stratégie ou décision. Suppose que ça a déjà échoué 6 mois plus tard et remonte dans le temps pour trouver tous les motifs. Produit un plan révisé avec les angles morts exposés. DÉCLENCHEURS OBLIGATOIRES : 'premortem ça', 'premortem mon', 'exécute un premortem', 'qu'est-ce qui pourrait tuer ça', 'stress-teste ce plan', 'qu'est-ce que je rate ici', 'trouve les angles morts'. DÉCLENCHEURS FORTS : 'qu'est-ce qui pourrait mal tourner', 'est-ce que je rate quelque chose', 'troue ce plan', 'où ça va casser', 'avocat du diable'. NE PAS déclencher sur des demandes simples de retour, des questions factuelles ou des demandes au Conseil LLM. DÉCLENCHER quand quelqu'un a un plan ou un engagement où le coût de se tromper est élevé."
ip-as-logo
s1dashu
Generate highly simplified personified IP mascot logos with Flat-first geometry, rounded heavy forms, two IP colors plus one background color by default, and continuous-gradient neo-skeuomorphic micro-volume. Use when creating an animal, creature, robot, ghost, plant, object, or other character as a minimal square logo or app-icon artwork, including when the agent should infer three product-relevant directions and propose six independent candidates for approval.
hindsight-recall
vectorize-io
Search long-term memory for relevant context from past coding sessions using Hindsight MCP tools
create-agent
vectorize-io
Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions.
hindsight-memory
vectorize-io
Long-term memory for the agent via Hindsight. Use to recall relevant past context before answering, retain durable facts as you learn them, and reflect over accumulated memory for the "why" behind a decision. Load whenever continuity across sessions matters — the user refers to earlier work, states a lasting preference, or asks a question that prior context could answer.
hindsight-coding-agent
vectorize-io
How this machine's Hindsight coding-agent memory works — the plugin behind the 🧠 banner. Use when the user says "store/remember this in hindsight", asks what the memory/knowledge pages are, wants to configure per-repo memory (disable, rename banks, git depth), or something memory-related looks broken.
hs-release
vectorize-io
Cut a core Hindsight release (vX.Y.Z) and open the changelog + blog PR. Use when asked to cut/start a release, bump the version, or publish a new Hindsight version.
code-review
vectorize-io
Review changed code against project standards. Checks for missing tests, dead code, type safety, lint issues, and coding conventions. Run after completing any implementation work.
hindsight-architect
vectorize-io
Expert memory architect. Understands your application, identifies where memory adds value, and produces an implementation plan with bank config, tag schema, and code.
querying-tophog
PostHog
Query tophog — the ingestion pipeline's heavy-hitter store in ClickHouse — to identify hot or expensive actors (team_id, distinct_id, session_id, partition) during incident triage. Use when investigating ingestion lag, a hot or lagging Kafka partition, expensive person processing, merge storms, or any "which team or distinct_id is causing this" question. Covers the internal Metabase access path (SSO via hogli), the tophog schema, and the cost-vs-volume query lens. Internal-only: results contain cross-customer identifiers.
optimizing-clickhouse-and-hogql-queries
PostHog
Workflow for optimizing ClickHouse and HogQL queries. Use when a HogQL query, query runner, insight, or report is too slow; when a hand-written ClickHouse query (via sync_execute or in a migration) is too slow; when ClickHouse times out or hits memory limits; when investigating a slow system.query_log row; or when reviewing a proposed HogQL printer change for performance. Covers extracting the ClickHouse SQL, common smells (FROM ... FINAL, JSONExtract over properties, missing skip indexes, self-joins, CTE blow-up), measuring against a real cluster, and applying the fix at the right layer (printer, query runner, or migration). Does NOT cover Postgres / Django ORM / app-database queries; those need pganalyze and the Postgres section of query-performance-optimization.md.
monitoring-ingestion-pipeline
PostHog
Guide for using the Grafana MCP to monitor and diagnose the Node.js ingestion pipeline workers in production. Use when investigating event lag, drops, pipeline errors, person/group processing, Kafka consumer health, Redis, Postgres, ClickHouse downstream health, or any ingestion worker question. Covers prod-us and prod-eu environments.
instrumenting-first-party-metrics
PostHog
"How to instrument PostHog's own Metrics product from PostHog-owned code — record counters, gauges, and histograms that land in posthog.metrics, the same way customers do. Use when adding application metrics in this monorepo (web, Celery, Temporal), when asked to push or ship metrics into posthog metrics, or when unsure whether the SDK in this environment supports posthog.metrics yet. Covers the environment decision (SDK-first per the public docs, OTel fallback when the SDK path is not available), the exact version gates per SDK, what is already wired internally, and how to validate metrics actually arrive."
analyzing-office365-audit-logs-for-compromise
mukul975
Parse Office 365 Unified Audit Logs via Microsoft Graph API to detect email forwarding rule creation, inbox delegation,
analyzing-cobaltstrike-malleable-c2-profiles
mukul975
Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract
analyzing-network-traffic-with-wireshark
mukul975
'Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns,
analyzing-memory-forensics-with-lime-and-volatility
mukul975
'Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility
analyzing-active-directory-acl-abuse
mukul975
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and
analyzing-cloud-storage-access-patterns
mukul975
Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS
analyzing-network-packets-with-scapy
mukul975
Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and
analyzing-linux-kernel-rootkits
mukul975
Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules),