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/validationgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plusWhat 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 | $0.00000 | $0.04992 |
| Opus 5 | $0.00000 | $0.02496 |
| Sonnet 5 | $0.00000 | $0.00998 |
| Haiku 4.5 | $0.00000 | $0.00499 |
Grade C, and why
validation scanned grade C with 1 finding 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 2d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- CONTRACT_START name: validation description: Independently verify analytical findings by re-deriving key numbers, checking arithmetic, cross-referencing data sources, and flagging common statistical errors. inputs: This is a copy
89% identical to validation — 47 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 368 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: Validation
Purpose
Independently verify analytical findings by re-deriving key numbers, checking arithmetic, cross-referencing data sources, and flagging common statistical errors — producing a pass/fail validation report with confidence ratings.
Inputs
- {{ANALYSIS_CODE}}: Path to the analysis code (SQL queries, Python scripts, or notebook) that produced the results. The agent will re-execute key queries independently.
- {{ANALYSIS_RESULTS}}: Path to the analysis report containing findings, numbers, charts, and conclusions. This is what gets validated.
- {{DATA_SOURCE}}: (optional) Connection string, file path, or database reference for the underlying data. If not provided, the agent will attempt to extract the data source from the analysis code.
- {{VALIDATION_SCOPE}}: (optional) Which findings to validate — "all" (default), or a comma-separated list of finding numbers (e.g., "1,3,5") for targeted validation. Use targeted validation when the full analysis is large and only specific findings need checking.
Workflow
Step 1: Inventory the claims
Read {{ANALYSIS_RESULTS}} end to end. Extract every quantitative claim into a numbered list. A "claim" is any statement that includes a specific number, percentage, ratio, trend direction, comparison, or ranking. For each claim, record:
- Claim ID: Sequential number (C1, C2, C3...)
- Statement: The exact text of the claim as it appears in the report
- Number(s): The specific values cited (e.g., "23%", "$1.2M", "3.5x")
- Source section: Where in the report the claim appears
- Derivable?: Whether the claim can be independently re-derived from the code and data (yes/no)
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.
- 2d ago First seen · 368 lines · 0 tokens per session scan C c72c7018fa96
validation 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 4,992 tokens. A static security scan graded it C with 1 finding (hidden instructions). It is 89% identical to validation, differing in 47 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.