publieople TOON — Token-Oriented Object Notation
The CLI
# encode JSON -> TOON
cat data.json | ~/.local/bin/toon
# decode TOON -> JSON
cat data.toon | ~/.local/bin/toon --decode
# non-JSON passes through unchanged (safe to pipe anything)
Requires ~/.local/bin/toon (Node wrapper around @toon-format/toon).
WHEN to auto-encode (you should pipe | toon)
Trigger conditions — at least 2 must match:
- Tool output is JSON and > 2KB
- Contains uniform array of objects (5+ rows, identical keys)
- Will be summarized/analyzed rather than written verbatim
- Mentioned "tokens", "context", "compress" in the task
- Repeated structure (logs, records, time-series)
WHEN to NOT encode
- Output goes to file/DB/other code (not LLM context)
- Small JSON (< 1KB) — overhead exceeds savings
- Deeply nested non-uniform — JSON-compact wins
- Downstream tool expects JSON (round-trip cost)
- Single record, not tabular
Self-check before piping
# count rows + keys homogeneity
cat X.json | jq 'if type == "array" then length else 0 end'
cat X.json | jq '[.[] | keys | join(",")] | unique | length'
# uniform = length matches array length, unique = 1
If uniform + ≥5 rows + >2KB → encode. Otherwise skip.
Format reminder
users[3]{id,name,email}:
1,Alice,a@x
2,Bob,b@x
3,Carol,c@x
[N] = array length, {fields} = column schema, CSV rows below.
Round-trip verification
echo '{"a":1}' | ~/.local/bin/toon | ~/.local/bin/toon --decode
# must equal '{"a":1}'
Honest caveat
This skill is descriptive — I must remember to apply it. True auto-firing
needs: (a) an AGENTS.md rule in the workdir, or (b) a Hermes tool-result
hook. Without one of those, I default to JSON unless explicitly told.