Analytics & Monitoring Agent Skills for Gemini CLI

Use this skill for AIRR-seq (Adaptive Immune Receptor Repertoire / VDJ-seq) data analysis with immunarch + immundata in R, including…

Step-by-step onboarding guide for connecting a new AI agent to Akasha.

Monitor and interact with Akasha's Nidra consolidation engine — the subsystem that automatically consolidates episodic memories into…

Use this skill when analyzing stocks, performing technical analysis, or evaluating market conditions.

Browse, slice, and analyze the curated American Reindustrialization directory — with diffs, geo clusters, sector...

Domain tips and workflow guidance for building AMI computation graphs via MCP tools.

Analyse the session that is running right now.

Assess whether structured data, query results, dashboards, or analytical evidence are trustworthy enough to use.

Systematically identify whether a GPU kernel is compute-bound, memory-bound, or latency-bound using roofline analysis, occupancy…

Analyses customer and user feedback in Dcipher - reviews, support tickets, survey responses, call transcripts, chat logs, community posts…

Pull and interpret production experiment query-performance data from the staff-only `/api/debug_ch_queries` endpoints backing the…

Analyze PostHog insights, dashboards, or teams beyond the current project by querying the prod Postgres replicas synced into the dogfood…

Write effective, consistent annotations on LLM/agent spans and traces, and coach the user on annotation practice.

Manages Arize users, organizations, spaces, projects, roles, role bindings, resource restrictions, and API keys via the ax CLI.

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features.

Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on…

Creates, manages, and queries Arize datasets and examples.

Handles LLM-as-judge and code evaluator workflows on Arize including creating/updating evaluators, running evaluations on spans or…

Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs.

Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations.

Profiles and tunes Ascend AI operators across on-device and simulation environments using msOpProf.