INDEX

INDEX is an agent for coding agents from ai-analyst-lab/ai-analyst-plus. It costs 0 tokens per session (1,992 once invoked), scanned A, original, MIT.

An index for an AI data-analysis system that lists shared variables and the agents that use them. The variables carry information such as dates, dataset names, business context, SQL patterns, corrections, and run folders.

In plain words
What is it for?
Use it when running or resuming an analysis pipeline, framing questions, routing them to agents, retrieving SQL patterns, or creating charts and presentations.
Why use it?
It provides a shared reference so different analysis agents use consistent names and pass information between pipeline stages.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/ai-analyst-lab/ai-analyst-plus/index
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plus

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for INDEX

README.md
[![agentmods](https://agentmods.dev/badge/agents/ai-analyst-lab/ai-analyst-plus/index.svg)](https://agentmods.dev/agents/ai-analyst-lab/ai-analyst-plus/index)
Your own site
<a href="https://agentmods.dev/agents/ai-analyst-lab/ai-analyst-plus/index"><img src="https://agentmods.dev/badge/agents/ai-analyst-lab/ai-analyst-plus/index.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,992 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01992
Opus 5 $0.00000 $0.00996
Sonnet 5 $0.00000 $0.00398
Haiku 4.5 $0.00000 $0.00199

Measured 5d ago against content hash a4a8e39804f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

INDEX scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/INDEX.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Index

System Variables (auto-resolved)

Variable Value Used in
{{DATE}} Current date, YYYY-MM-DD All agent output filenames
{{DATASET_NAME}} Short name derived from data path or user input File naming, report headers
{{BUSINESS_CONTEXT_TITLE}} Short title derived from {{BUSINESS_CONTEXT}} Question brief header
{{RUN_ID}} Unique run identifier (YYYY-MM-DD_question-slug) Run Pipeline, Resume Pipeline
{{RUN_DIR}} Per-run output directory path All agents during pipeline
{{SQL_PATTERNS}} Archaeology-retrieved SQL patterns Analysis agents
{{CORRECTIONS}} Logged corrections for current context Analysis agents
{{LEARNINGS}} Category-specific learnings Question Framing, Storytelling
{{ENTITY_INDEX}} Disambiguation index Question Router
{{ORG_CONTEXT}} Business context (glossary, products, teams) Question Framing, Storytelling
{{THEME}} Active theme name Chart Maker, Deck Creator
{{CONTEXT}} Presentation context (workshop/talk/analysis) Story Architect, Deck Creator
{{STORYBOARD}} Story Architect output Chart Maker, Storytelling
{{FIX_REPORT}} Visual Design Critic feedback Chart Maker (fix pass)
{{DECK_FILE}} Generated deck path Visual Design Critic
{{CONFIDENCE_GRADE}} Validation confidence score (A-F) Storytelling, Deck Creator

Agents

Agent Path Invoke When
Question Framing agents/question-framing.md User provides a business problem to analyze
Hypothesis agents/hypothesis.md Questions are framed, need testable hypotheses
Data Explorer agents/data-explorer.md Need to understand what data exists in a source
Descriptive Analytics agents/descriptive-analytics.md Need to analyze a dataset (segmentation, funnels, drivers)
Overtime / Trend agents/overtime-trend.md Need time-series analysis or trend identification
Cohort Analysis agents/cohort-analysis.md Need cohort retention curves, LTV analysis, or vintage comparison
Root Cause Investigator agents/root-cause-investigator.md Initial analysis found an anomaly — need to drill down iteratively to find the specific root cause
Opportunity Sizer agents/opportunity-sizer.md Root cause identified or opportunity found — quantify the business impact with sensitivity analysis
Experiment Designer agents/experiment-designer.md Need to test a causal hypothesis — designs A/B tests or quasi-experimental analyses with power estimation and decision rules
Story Architect agents/story-architect.md Analysis is complete — designs the storyboard (narrative beats + visual mapping) before any charting. Pass {{CONTEXT}} for workshop/talk closing sequences.
Chart Maker agents/chart-maker.md Need to generate a specific chart.
Visual Design Critic agents/visual-design-critic.md After Chart Maker generates charts — reviews against SWD checklist. After Deck Creator — reviews slide-level design with {{DECK_FILE}} and {{THEME}}.
Narrative Coherence Reviewer agents/narrative-coherence-reviewer.md After Story Architect produces the storyboard, before charting — reviews story flow, beat structure, and Closing beats if present
Storytelling agents/storytelling.md Analysis and charts are complete, need a narrative
Cross-Verification agents/cross-verification.md After analysis (step 6.5) — verify analytical claims via independent calculation paths (Types A-D: boundary, parts-to-whole, ratio recompute, algebraic identity). Includes reproducibility checks.
Receipt Generator agents/receipt-generator.md After close-the-loop (step 18.5, conditional) — full audit trail for Reproduce audience. Query log, validation, cross-verification, reproducibility. Tier 3 or /export receipt.
Notion Export agents/notion-export.md Export analysis to Notion page with charts, data stamps, provenance toggles, Analysis Gallery integration. Standalone, invoked via /export notion.
Validation agents/validation.md Need to verify findings before presenting
Deck Creator agents/deck-creator.md Need to create a presentation from analysis. Supports {{THEME}} (analytics-dark) and {{CONTEXT}} (workshop/talk closing sequence).
Comms Drafter agents/comms-drafter.md Need stakeholder communications (Slack summary, email brief, exec summary). Non-critical — pipeline continues if this fails.
Google Slides Creator agents/google-slides-creator.md Need a live, editable Google Slides deck (alternative to Deck Creator). Uses {{NARRATIVE}}, {{STORYBOARD}}, optional {{THEME}} (light/dark) and {{DECK_TITLE}}. Requires Google Workspace MCP.
Google Slides Reviewer agents/google-slides-reviewer.md Auto-invoked after Google Slides Creator -- reviews formatting (overflow, overlap, fonts, colors) and self-applies fixes. Max 2 iterations.
Google Doc Creator agents/google-doc-creator.md Need a live, editable Google Doc from analysis narrative + charts. Handles image placement (bottom-to-top), heading hierarchy, and formatting. Requires Google Workspace MCP.
Google Doc Reviewer agents/google-doc-reviewer.md Auto-invoked after Google Doc Creator -- reviews heading hierarchy, image placement, spacing, formatting. Self-applies fixes. Max 2 iterations.
Experiment Analyzer agents/experiment-analyzer.md Full experiment analysis — 8-question framework: SRM → treatment effect → reliability → segments → duration → ROI → recommendation → follow-ups. Takes raw experiment data, produces nuanced conditional recommendation.
Experiment Readout agents/experiment-readout.md Transform experiment analysis into stakeholder-ready readout with executive summary, visualizations, per-segment decisions, ramp plan, and follow-up experiments. Adapts to audience (executive/technical/cross-functional).
Story Extractor agents/story-extractor.md Find the 1-3 stories worth telling in messy input (analysis docs, data tables, bad decks). Scores findings on surprise, impact, relevance, evidence strength. The "editorial judgment" agent.
Presentation Doctor agents/presentation-doctor.md Orchestrator: diagnose → extract → transform. Coordinates deck-critique, story-extractor, and deck-rescue/slide-transform into one pipeline. Includes presenter coaching notes.
Hypothesis Sharpener agents/hypothesis-sharpener.md Takes a vague hunch and transforms it into a testable hypothesis with precise metrics, comparison groups, natural experiments, and accept/reject criteria. Called by /analysis-design skill.
Confound Scanner agents/confound-scanner.md Adversarial agent that finds threats to validity — concurrent changes, data quality issues, selection biases. Argues AGAINST the hypothesis to make the investigation airtight. Called by /analysis-design skill.
Feedback Synthesizer agents/feedback-synthesizer.md Takes V1 findings + messy stakeholder feedback, categorizes it (methodological flaws, missing confounds, reframes, new analyses), and produces a structured V2 investigation plan with stakeholder answer map. Called by /analysis-design skill.
Experiment Interpreter agents/experiment-interpreter.md Walks the Result Interpretation Tree (positive/null/negative/mixed) and applies EwL framework (Ship/Abort/Learn/Invalid). Called by /experiment interpret.
Experiment Monitor agents/experiment-monitor.md Daily monitoring: SRM trending, guardrail status, sample accumulation, power projection. Called by /experiment monitor.
Causal Method Selector agents/causal-method-selector.md Interactive 8-question decision tree to recommend the right causal method (DiD, PSM, pre-post, regression). Called by /causal select.
Causal Analyzer agents/causal-analyzer.md Executes the selected causal method using helpers/experiment_stats/causal/. Called by /causal analyze.
Causal Assumption Checker agents/causal-assumption-checker.md Per-method diagnostic battery (parallel trends, common support, balance). Called by /causal check.
Causal Sensitivity agents/causal-sensitivity.md Rosenbaum bounds, E-value, placebo tests with plain-language translations. Called by /causal sensitivity.
Causal Interpreter agents/causal-interpreter.md Places estimate on the confidence ladder and synthesizes verdicts. Called by /causal report.
Causal Report Generator agents/causal-report-generator.md Full report with mandatory caveats per method (non-negotiable). Called by /causal report.

Read the full file on GitHub · 65 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 65 lines · 0 tokens per session scan A a4a8e39804f0

Subscribe to this mod's changes

INDEX is an agent published in the GitHub repository ai-analyst-lab/ai-analyst-plus (19 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,992 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.