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Data & AI

Machine learning, LLMs, and data processing.

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llm-ai

57

writer-context-pack

Build per-H3 writer context packs (NO PROSE): merge briefs + evidence packs + anchor facts + allowed citations into a single deterministic JSONL, so drafting is less hollow and less brittle. **Trigger**: writer context pack, context pack, drafting pack, paragraph plan pack, 写作上下文包. **Use when**: `outline/subsection_briefs.jsonl` + `outline/evidence_drafts.jsonl` + `outline/anchor_sheet.jsonl` exist and you want to make C5 drafting easier/more consistent. **Skip if**: upstream evidence is missing or scaffolded (fix `paper-notes` / `evidence-binder` / `evidence-draft` / `anchor-sheet` first). **Network**: none. **Guardrail**: NO PROSE; do not invent facts/citations; only use citation keys present in `citations/ref.bib`.

WILLOSCAR

data-ai

machine-learning

56

forecast-modeling

Use when designing, tuning, or auditing revenue forecast models.

gtmagents

data-ai

data-analysis

56

executive-kpi-briefings

Template pack for summarizing BI insights for ELT/board stakeholders.

gtmagents

data-ai

llm-ai

56

trend-research

Use when identifying cultural moments, audio trends, memes, or creator collaborations to inform social content.

gtmagents

data-ai

llm-ai

56

objection-handling

Use when preparing responses to prospect objections during outbound, discovery, or follow-up conversations.

gtmagents

data-ai

llm-ai

56

skill-name

{{ when to invoke this skill }}

gtmagents

data-ai

llm-ai

56

nav-compact

Clear conversation context while preserving knowledge via context marker. Use when user says "clear context", "start fresh", "done with this task", or when approaching token limits.

alekspetrov

data-ai

llm-ai

56

aimds

AI Manipulation Defense System implementation with Midstream, AgentDB, and lean-agentic

ruvnet

data-ai

llm-ai

56

nav-profile

Manage user preferences and corrections for bilateral modeling. Auto-learns from session corrections. Use when user says "save my preferences", "remember I like...", or auto-triggers after corrections.

alekspetrov

data-ai

machine-learning

56

deal-quality-model

Scoring system for opportunity hygiene, win likelihood, and inspection prioritization.

gtmagents

data-ai

machine-learning

56

signal-scoring

Use to design composite intent scoring models with decay, weighting, and governance.

gtmagents

data-ai

machine-learning

56

forecast-discipline

Use to drive consistent forecast methodology, grading, and inspection cadences.

gtmagents

data-ai

data-analysis

56

character-reference-sheet

Generates a 3:2 aspect ratio character reference sheet with three columns: detailed portrait, full-body front view, and full-body back view, mirroring the exact style and material details of the source.

ShinChven

data-ai

llm-ai

55

consult-llm

Use it when the user asks to "ask gemini", "ask codex", or "ask in browser"

raine

data-ai

llm-ai

55

discover-research

Gateway skill for research methodology - automatically loads relevant research skills based on task context

rand

data-ai

data-analysis

55

data-metabase

Metabase REST API automation: auth, export/upsert cards and dashboards, visualization_settings. Use when scripting Metabase via API.

vasilyu1983

data-ai

data-analysis

55

data-analysis

Analyze datasets to extract insights through statistical methods, trend identification, hypothesis testing, and correlation analysis.

seb1n

data-ai

data-analysis

55

data-visualization

Create clear, effective charts and dashboards from structured data using matplotlib, seaborn, and plotly.

seb1n

data-ai

data-analysis

55

dv-query

Bulk reads, multi-page iteration, and analytics using the Python SDK and Web API. Use when: "query records", "read data", "bulk read", "all records", "iterate records", "expand lookup", "cross-table query", "join tables", "aggregate", "group by", "average", "sum", "count with HAVING", "$apply", "N:N expand", "notebook", "pandas", "DataFrame", "analyze data", "load into dataframe". Do not use when: MCP is sufficient (simple filter, single-record read, small result set — use MCP first), creating or modifying records (use dv-data), creating tables or columns (use dv-metadata).

microsoft

data-ai

data-analysis

55

explore-dataset

Explore an Axiom dataset to understand its schema, fields, volume, and patterns. Use when discovering a new dataset, investigating data structure, or understanding what data is available.

axiomhq

data-ai

data-analysis

55

axiom-apl

APL query language reference for Axiom. Provides operators, functions, patterns, and CLI usage. Auto-invoked by specialized Axiom skills when writing or debugging APL queries.

axiomhq

data-ai

data-analysis

55

exploratory-data-analysis

Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling.

seb1n

data-ai

data-analysis

54

ux-researcher-designer

UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user research, persona creation, journey mapping, and design validation.

viralcode

data-ai

data-analysis

54

snowflake-create-hybrid-table

Consult Snowflake CREATE HYBRID TABLE parameter reference before generating any CREATE HYBRID TABLE DDL.

Gyrus-Dev

data-ai

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