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 imMamdouhaboammar/get-fable --skill fable-datavizgit clone --depth 1 https://github.com/imMamdouhaboammar/get-fableWrote 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/immamdouhaboammar/get-fable/fable-dataviz)<a href="https://agentmods.dev/skills/immamdouhaboammar/get-fable/fable-dataviz"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/fable-dataviz/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/immamdouhaboammar/get-fable/fable-dataviz"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/fable-dataviz.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 | $0.00115 | $0.01884 |
| Opus 5 | $0.00057 | $0.00942 |
| Sonnet 5 | $0.00023 | $0.00377 |
| Haiku 4.5 | $0.00012 | $0.00188 |
Grade A, and why
fable-dataviz 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 7d 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 — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fable DataViz
Turn data into a visual claim that is easy to read without changing what the data actually says.
Mission
A chart is an argument about magnitude, trend, distribution, relationship, uncertainty, or composition. The first job is to choose a visual encoding that matches that question. The second is to preserve statistical meaning. Styling comes after both.
A valid SVG with attractive colors can still be a bad visualization if it truncates axes deceptively, aggregates incompatible groups, hides missing data, implies causality from correlation, or invents precision the source does not support.
Activate When
- a metric/trend/distribution/comparison/relationship needs visual explanation;
- benchmark/eval results need charts or stat graphics;
- a report/artifact needs an evidence-backed visual;
- raw data must be transformed into SVG/chart code or a visual specification.
Do Not Activate When
- there is no actual data and the request would require inventing values;
- a plain table is more accurate/readable for a small lookup task;
- the core task is document structure rather than visual encoding (
fable-artifact); - the user requests an illustrative image rather than a data visualization.
Question Classification
| Question | Useful first encoding | Typical misuse |
|---|---|---|
| Compare categories | bar/dot plot | pie with many similar slices |
| Trend over ordered time | line/area with careful baseline | unordered category line chart |
| Distribution | histogram/box/violin/dot | average-only bar |
| Relationship | scatter/bubble with scale caveats | dual-axis correlation theater |
| Part-to-whole | stacked bar/100% bar; limited pie | sum components that are not one whole |
| Ranking | sorted bar/dot | alphabetic order hiding rank |
| Single KPI + context | stat + baseline/change | giant number without denominator/timeframe |
| Uncertainty | interval/band/error bars | precise point with hidden variance |
Protocol
Stage 1 — Establish data provenance and semantic contract
Record:
- source/dataset/version/time window;
- unit and denominator;
- category/time definitions;
- missing/null semantics;
- whether values are counts, rates, percentages, currency, estimates, or modeled outputs;
- uncertainty/precision available.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 220 lines · 115 tokens per session scan A e6aa969cdf3f
fable-dataviz is a skill published in the GitHub repository imMamdouhaboammar/get-fable (4 stars, last pushed today), licensed MIT. It adds 115 tokens to every session and 1,884 once invoked, about $0.0006 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 2026-09-05.
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