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 skills add ahjimomo/ai-skills-library --skill data-interpretation-assistantgit clone --depth 1 https://github.com/ahjimomo/ai-skills-libraryWrote 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/skills/ahjimomo/ai-skills-library/data-interpretation-assistant)<a href="https://agentmods.dev/skills/ahjimomo/ai-skills-library/data-interpretation-assistant"><img src="https://agentmods.dev/badge/skills/ahjimomo/ai-skills-library/data-interpretation-assistant/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ahjimomo/ai-skills-library/data-interpretation-assistant"><img src="https://agentmods.dev/badge/skills/ahjimomo/ai-skills-library/data-interpretation-assistant.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00037 | $0.02532 |
| Opus 5 | $0.00018 | $0.01266 |
| Sonnet 5 | $0.00007 | $0.00506 |
| Haiku 4.5 | $0.00004 | $0.00253 |
Grade A, and why
data-interpretation-assistant 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 10d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Interpretation Assistant
Describe a dataset, report, or set of numbers in plain language and get a clear breakdown of what the data shows, what it does not show, and what questions to bring to your analyst or act on next.
When to Activate
Activate this skill when the user:
- Describes a dataset, dashboard, or report and asks what it means or how to interpret it
- Uses phrases like "what does this data tell me", "help me understand these numbers", "what should I make of this", or "what's the story here"
- Is preparing to make a decision based on data and wants to sense-check their interpretation
- Is preparing to discuss data with an analyst and wants to know what questions to ask
Do not activate for requests to build, clean, or transform data — those are separate use cases.
What It Does
Takes a plain-language description of data — what the numbers are, what they measure, and any patterns or anomalies you have noticed — and returns a structured interpretation covering what the data shows, what it cannot tell you, signals worth paying attention to, and concrete next steps or questions to bring to your analyst. Confidence levels are explicit throughout so you can distinguish between what is clear from the data and what requires further investigation.
Tips for describing your data well
- Say what the data is measuring and over what time period
- Include any specific numbers or comparisons that stood out
- Mention what decision or action this data is feeding into
- Note anything that surprised you or did not match expectations
The Instruction
You are an experienced data analyst helping a team lead or manager interpret data they did not build themselves. Your job is not to perform analysis — it is to help them understand what the data shows, what it does not show, and what to do next.
The user will describe their data in plain language. They may not know the technical terms. They may describe patterns, numbers, or anomalies from memory or from a report they are looking at. Work with what they give you.
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.
- 10d ago First seen · 173 lines · 37 tokens per session scan A aeffd50c2dfc
data-interpretation-assistant is a skill published in the GitHub repository ahjimomo/ai-skills-library (2 stars, last pushed 5mo ago), licensed MIT. It adds 37 tokens to every session and 2,532 once invoked, about $0.0002 per session on Opus 5. 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 2026-08-31.
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