AI & ML

rifteo Bundle

Documents the current state of an active pentest engagement so the next agent session can continue without losing context, covering findings, coverage, next steps, and open threads. Trigger when the user says "handoff", "save progress", "pick this up next session", or "summarize the engagement", when the context window is getting long and work needs to continue in a fresh session, or at the end of a testing day or shift change.

seva8756 Bundle

Use MCP tools when the user asks for data or actions from configured MCP servers.

ankit1598 Skill

Default terse “caveman-style” assistant prose for explanations and reasoning; modes lite, full, ultra, and optional wenyan tiers; persists until stop caveman or normal mode. Use for every technical reply unless the user turns it off or Auto-Clarity applies. Commit message suggestions still follow the git-commit skill.

ankit1598 Skill

Creates new agent skills following project conventions — kebab-case folder names, 100-line SKILL.md limit, third-person descriptions with trigger keywords, and .artifacts/ awareness for output-producing skills. Use when creating a new skill, writing a skill, or asked "add a skill for X", "make a skill that...", "new skill for X".

ankit1598 Bundle

Writes ADR-lite decision records under .artifacts/decisions/ as DECISION_YYYYMMDD_TITLE.md (optional entity subfolder). Use when recording an architecture, product, data-model, security, dependency, or workflow decision, or when the user says "decision record", "ADR", "record the decision", or "log this decision".

agentcorp-inc Bundle

Find where an AI/LLM application is failing in production and surface the failure patterns, working from real traces. Use when someone wants to understand what's going wrong with an AI feature, find and categorize failure modes, triage errors, or investigate quality issues (wrong answers, ignored instructions, hallucinations, tool misuse) — "what's failing in my agent", "surface error patterns", "why are the responses bad", "find the common failure modes", "what should I fix next". Covers scoping to one use case, finding failing traces by whichever signal fits the context (code errors, metric outliers, trace-type slices, manual review, existing-eval spikes, clustering), and reading them into a ranked failure taxonomy.

homeowmorphism Bundle

Teach concepts, answer conceptual follow-ups, provide step-by-step explanations, and design practice that adapts to the learner's demonstrated understanding. Use for tutoring and substantive learning questions across topics; maintain an optional, user-inspectable learner model shared with pair-programming. Routine factual answers and requests to implement work do not need a teaching session.

steve-t-hill Bundle

Expert guidance and automated agent protocol for building BigQuery Labeled Property Graphs (LPG), querying with GQL (ISO standard), executing a 5-step relational-to-graph translation (Golden Queries, Topology Extraction, ML.DESCRIBE_DATA profiling, Logic Mapping, DDL Generation), optimizing multi-hop queries, and implementing graph measures. Use this skill when: 1. Translating existing BigQuery relational tables (99% of cases) or unstructured documents (1% of cases) into CREATE PROPERTY GRAPH DDL. 2. Executing automated agent pipelines for topology extraction (via Data Catalog MCP) and statistical profiling (ML.DESCRIBE_DATA) to fold lookup tables into properties and discover hidden FKs. 3. Writing high-performance GQL queries, handling super nodes, using VECTOR_SEARCH with graph traversals, or querying graph measures via GRAPH_EXPAND and AGG().

agentcorp-inc Bundle

Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.

gee9999 Bundle

Model and improve Proto's wholesale catalogue, trader accounts, pricing, stock, orders, fulfilment, and admin workflows.

agentcorp-inc Skill

Build n8n workflows using the Pinecone Assistant node or Pinecone Vector Store node. Use when building RAG pipelines, chat-with-docs workflows, configuring Pinecone nodes in n8n, troubleshooting Pinecone n8n nodes, or asking about best practices for Pinecone in n8n.

agentcorp-inc Skill

Query integrated indexes using text with Pinecone MCP. IMPORTANT - This skill ONLY works with integrated indexes (indexes with built-in Pinecone embedding models like multilingual-e5-large). For standard indexes or advanced vector operations, use the CLI skill instead. Requires PINECONE_API_KEY environment variable and Pinecone MCP server to be configured.

agentcorp-inc Skill

Pick the right y-axis unit when creating or updating a TrendsQuery insight via `posthog:insight-create` or `posthog:insight-update`. Use when the agent is about to add a `formula` purely to convert units (e.g. dividing seconds by 60 to display minutes), when a `math_property` is a duration, currency, ratio, or large count, or whenever the user mentions "format the y-axis", "duration", "seconds", "minutes", "hours", "milliseconds", "ms", "percentage", "currency", "decimals", "axis label", or "axis unit" in the context of a graph insight.

agentcorp-inc Skill

Create a recurring AI-generated PostHog report — schedule a free-text prompt to run on a cron, with the LLM-synthesized markdown delivered to email or Slack on each tick. Use when the user wants a recurring AI summary of X on any cadence (daily, weekly, monthly, yearly) rather than a one-off report. (To attach an AI summary to an existing insight/dashboard subscription instead of a free-text prompt, see `managing-subscriptions` and its `summary_enabled` option.)

gee9999 Bundle

Use when investigating Proto's architecture, route dependencies, cross-service links, dead code, or difficult catalogue/stock bugs; optionally use a locally audited codebase-memory-mcp installation for structural queries.

agentcorp-inc Bundle

Interactive Pinecone quickstart for new developers. Choose between two paths - Database (create an integrated index, upsert data, and query using Pinecone MCP + Python) or Assistant (create a Pinecone Assistant for document Q&A). Use when a user wants to get started with Pinecone for the first time or wants a guided tour of Pinecone's tools.

agentcorp-inc Bundle

Build your app's primary user interface embedded in the Shopify admin. If the prompt just mentions `Polaris` and you can't tell based off of the context what API they meant, assume they meant this API.

agentcorp-inc Skill

Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user LLM cost, user-level cost drivers, or patterns behind high AI observability spend.

agentcorp-inc Bundle

Author, save, and edit email templates in the PostHog workflows library — compose email design JSON with Liquid personalization and create and round-trip-edit templates over MCP. Use when asked to design, build, update, or fix an email template for workflows, broadcasts, or campaigns.

agentcorp-inc Skill

Investigate AI observability evaluations — `hog` (deterministic code-based), `llm_judge` (LLM-prompt-based), and `sentiment` (user-message sentiment). Find existing evaluations, inspect their configuration, run them against specific generations, query individual results, and generate AI-powered summaries for boolean pass/fail runs. Use when the user asks to debug why an evaluation is failing, surface common failure modes, compare results across filters, dry-run a Hog evaluator, prototype a new LLM-judge prompt, inspect sentiment classifications, or manage the evaluation lifecycle.

agentcorp-inc Bundle

Create, ingest into, and query a Pinecone full-text-search (FTS) index using the preview API (2026-01.alpha, public preview). Use when the user or agent asks to build a text search index on Pinecone, add dense or sparse vector fields, ingest documents, construct score_by clauses (text / query_string / dense_vector / sparse_vector), or compose with text-match filters ($match_phrase / $match_all / $match_any). Ships `scripts/ingest.py` for safe bulk ingestion (batch_upsert + error inspection + readiness polling); query construction is documented inline in this skill — write `documents.search(...)` calls directly, validated against `pc.preview.indexes.describe(...)` output.

agentcorp-inc Bundle

Postman concepts and MCP tool guidance. Loaded when working with Postman MCP tools to make better decisions about tool selection and workarounds.

agentcorp-inc Skill

Skill-hygiene scout for the team's PostHog skills store, read entirely via the MCP skill tools. Watches recently-changed skills — plus a slow rotation over the most-used, highest-leverage ones — for statically-verifiable authoring violations: vague descriptions, bloated bodies, dead bundled-file links, kitchen-sink scope, committed secrets. Files each non-compliant skill as a report in the inbox, with the copy-ready fix inside.

agentcorp-inc Bundle

Connect third-party AI agents (OpenAI, Bedrock, LangChain, Microsoft Foundry) to Twilio's communication channels using the Twilio Agent Connect SDK. Covers identity resolution, memory and context management via Conversation Memory, conversation orchestration via Conversation Orchestrator, multi-channel handling (Voice, SMS, RCS, WhatsApp, Chat), and AI-to-human escalation. Use this skill when integrating an existing LLM agent with Twilio services.

agentcorp-inc Bundle

Author continuously-running online evaluations in PostHog AI observability, grounded in a real failure mode you've identified. Use when the user wants an evaluation that automatically scores new `$ai_generation` events going forward — "create an eval to catch X", "continuously check that responses do Y", "turn this failure into an eval". Covers choosing the eval type (hog / llm_judge / sentiment), gating on the team's provider key before an llm_judge eval, scoping which events fire via conditions (property filters + rollout sampling), creating it disabled, verifying scope, and enabling. Finding and ranking the failure modes worth evaluating is its own job — use exploring-ai-failures first. To debug or manage evaluations that already exist, use exploring-llm-evaluations.

agentcorp-inc Skill

Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).

agentcorp-inc Bundle

Investigate LLM spend in PostHog — total cost over time, cost by model, provider, user, trace, or custom dimension, token and cache-hit economics, and cost regressions. Use when the user asks "how much are we spending on LLMs?", "which model / user / feature is most expensive?", "why did cost spike?", wants to build a cost dashboard or alert, or pastes a trace URL and asks about its cost.

agentcorp-inc Bundle

Fallback Airwallex skill — works with the Airwallex CLI or the Airwallex MCP server. Use ONLY when no dedicated workflow skill matches the task. Covers ad-hoc operations (list, get, update, delete, void, cancel), general Airwallex API questions, troubleshooting, and domains not covered by a workflow skill (payment links, refunds, disputes, spend management, financial reports). Do NOT load this skill alongside a workflow skill — each workflow skill is self-contained. For invoices/billing/coupons/meters/credit notes use contract-to-billing, for suppliers/beneficiaries use beneficiary-creation, for cards use card-provisioning, for balances/FX/cashflow use manage-cashflow.

agentcorp-inc Skill

Best practices for agents managing PostHog skills via the MCP `skill-*` tools — how to discover, read, create, update, and refactor skills efficiently, especially large skills with many bundled files. Use whenever you are about to call any `skill-*` tool, asked to author or edit a shared skill, or troubleshoot why a skill write was rejected. Pairs with `skills-store` (which covers the raw tool surface) by adding the decision-tree, efficiency, and pitfall guidance.

agentcorp-inc Bundle

MUST be used first when prompts mention Metafields or Metaobjects. Use Metafields and Metaobjects to model and store custom data for your app. Metafields extend built-in Shopify data types like products or customers, Metaobjects are custom data types that can be used to store bespoke data structures. Metafield and Metaobject definitions provide a schema and configuration for values to follow.

agentcorp-inc Bundle

Signals scout for PostHog AI observability. Watches LLM traces for cost, latency, error, volume, and eval-performance regressions, sliced by the dimensions it discovers over time, and files each validated regression as a report in the inbox.

agentcorp-inc Bundle

Signals scout for PostHog MCP tool calls. Watches $mcp_tool_call telemetry for tools that need improvement — high, broad-reach failure rates, retry/hammering that betrays a confusing schema, slow or context-bloating responses — and files each validated tool-quality finding as a report in the inbox; otherwise writes durable memory and closes out empty. Adapts to which fields the project actually captures.

agentcorp-inc Bundle

Configure (or troubleshoot) an AI coding agent or CLI to route through the Salesforce Models API using a signed OrgJWT. Use this skill when pointing an agent at the Salesforce model endpoint (api.salesforce.com/ai/gpt/v1), setting up OrgJWT / Bedrock-mode auth, wiring the agent's settings, API-key helper, and credentials file for the Salesforce endpoint, or fixing Models API 401 / 404 / "model not available" errors. DO NOT TRIGGER when the user needs to create or configure the Salesforce Connected App itself (use integration-connectivity-connected-app-configure) or set up Named Credentials / callout auth (use integration-connectivity-generate).

vroind-ausm-all Skill

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

silviobeer Bundle

Test features end-to-end against acceptance criteria, find bugs, perform security audit, and gate unnecessary implementation complexity through a simplicity review. Use when: (1) implementation is complete and needs testing before release, (2) feature needs end-to-end validation against acceptance criteria, (3) security or maintainability risk needs review. The QA agent finds and documents bugs — it NEVER fixes them. Not for: unit testing during development (that's part of executing), code review-only requests, or deployment.

silviobeer Bundle

Test features end-to-end against acceptance criteria, find bugs, perform security audit, and gate unnecessary implementation complexity through a simplicity review. Use when: (1) implementation is complete and needs testing before release, (2) feature needs end-to-end validation against acceptance criteria, (3) security or maintainability risk needs review. The QA agent finds and documents bugs — it NEVER fixes them. Not for: unit testing during development (that's part of executing), code review-only requests, or deployment.