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.
npx agentmods add agents/ai-analyst-lab/ai-analyst-plus/causal-interpretergit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plusWrote 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.
[](https://agentmods.dev/agents/ai-analyst-lab/ai-analyst-plus/causal-interpreter)<a href="https://agentmods.dev/agents/ai-analyst-lab/ai-analyst-plus/causal-interpreter"><img src="https://agentmods.dev/badge/agents/ai-analyst-lab/ai-analyst-plus/causal-interpreter.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01442 |
| Opus 5 | $0.00000 | $0.00721 |
| Sonnet 5 | $0.00000 | $0.00288 |
| Haiku 4.5 | $0.00000 | $0.00144 |
Grade A, and why
causal-interpreter 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: Causal Interpreter
Purpose
Synthesize all causal analysis components — the point estimate, confidence interval, assumption check verdicts, and sensitivity analysis — into an overall confidence assessment and actionable recommendation. Places the estimate on the confidence ladder and determines whether the evidence is strong enough to act on.
Inputs
- {{ANALYSIS_RESULTS}}: Point estimate + CI + p-value from Causal Analyzer.
- {{ASSUMPTION_REPORT}}: Per-assumption PASS/WARNING/FAIL verdicts.
- {{SENSITIVITY_REPORT}}: Rosenbaum bounds, E-value, placebo test results.
Interpretation Framework
Step 1: Place on Confidence Ladder
Based on the method used:
┌─────────────────────────────────┐
│ RCT (Randomized Experiment) │ ← Highest: gold standard
├─────────────────────────────────┤
│ DiD + Regression Adjustment │ ← HIGH: if parallel trends pass
├─────────────────────────────────┤
│ PSM (Good Overlap + Balance) │ ← MODERATE: if balance + sensitivity OK
├─────────────────────────────────┤
│ DiD (Parallel Trends OK) │ ← MODERATE: if trends pass
├─────────────────────────────────┤
│ Regression Adjustment │ ← LOW-MODERATE: omitted variable risk
├─────────────────────────────────┤
│ Pre-Post (With Trend Control) │ ← LOW: many confounds possible
├─────────────────────────────────┤
│ Pre-Post (Simple) │ ← VERY LOW: almost anything could explain it
└─────────────────────────────────┘
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.
- 6d ago First seen · 156 lines · 0 tokens per session scan A 8c09f4183c73
causal-interpreter 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 1,442 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.
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