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 skills/soulcodex/agentic/json-to-toonnpx skills add soulcodex/agentic --skill json-to-toongit clone --depth 1 https://github.com/soulcodex/agenticWrote 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/soulcodex/agentic/json-to-toon)<a href="https://agentmods.dev/skills/soulcodex/agentic/json-to-toon"><img src="https://agentmods.dev/badge/skills/soulcodex/agentic/json-to-toon.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 | $0.00088 | $0.01377 |
| Opus 5 | $0.00044 | $0.00688 |
| Sonnet 5 | $0.00018 | $0.00275 |
| Haiku 4.5 | $0.00009 | $0.00138 |
Grade A, and why
json-to-toon 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JSON to TOON Transformation Skill
Convert JSON input into TOON (Token-Oriented Object Notation) to achieve 30–70% token reduction, making it ideal for use in LLM prompts, RAG pipelines, and any context-window-sensitive application.
Step 1 — Load the Specification
Read toon-spec-reference.md (in this skill's directory). It contains the
complete encoding rules you must apply throughout this skill.
Step 2 — Assess the Input
Inspect the JSON the user has provided:
- Identify the root type: is it an object, array of uniform objects, array of mixed objects, or a primitive array?
- Scan for high-repetition patterns: arrays of objects with identical keys are prime candidates for tabular format (biggest token savings).
- Flag any values that require quoting: strings containing
,,:,[,{,-at start, leading/trailing spaces, or values that look like booleans/numbers/null. - Note depth: deeply nested structures may benefit most from TOON's indentation-based nesting (no closing braces).
Output a brief one-line assessment: e.g.
"Root object with 3 tabular arrays and 2 nested objects — expect ~55% token reduction."
Step 3 — Choose Array Format for Each Array
For every array in the input, apply this decision tree:
Is every element a primitive (string, number, boolean, null)?
YES → Inline format: key[N]: v1,v2,v3
Are ALL elements objects AND do they share identical top-level keys AND
are all their values primitives (no nested objects or arrays)?
YES → Tabular format: key[N]{f1,f2,f3}:
v1,v2,v3
v4,v5,v6
Otherwise (different keys, nested values, mixed types)
→ List format: key[N]:
- field: value
field2: value2
Use the field order of the first object for all tabular rows. Never re-order fields.
Step 4 — Encode the Full Structure
Walk the JSON top-down and apply the rules from toon-spec-reference.md:
What ships with it
1 file 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.
- 6d ago First seen · 159 lines · 88 tokens per session scan A 59ac49be61b2
json-to-toon is a skill published in the GitHub repository soulcodex/agentic (10 stars, last pushed yesterday), licensed MIT. It adds 88 tokens to every session and 1,377 once invoked, about $0.0004 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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