Borrowing it
Nothing to install: this file belongs to littlebearapps/untether. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/littlebearapps/untether/master/.claude/skills/jsonl-subprocess-runner/SKILL.mdgit clone --depth 1 https://github.com/littlebearapps/untetherWrote 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/littlebearapps/untether/jsonl-subprocess-runner)<a href="https://agentmods.dev/skills/littlebearapps/untether/jsonl-subprocess-runner"><img src="https://agentmods.dev/badge/skills/littlebearapps/untether/jsonl-subprocess-runner/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/littlebearapps/untether/jsonl-subprocess-runner"><img src="https://agentmods.dev/badge/skills/littlebearapps/untether/jsonl-subprocess-runner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 242 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00052 | $0.02494 |
| Opus 5.5 | $0.00021 | $0.00998 |
| Sonnet 5.5 | $0.00010 | $0.00499 |
| Haiku 4.5 | $0.00005 | $0.00249 |
Grade A, and why
jsonl-subprocess-runner 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 18d 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 — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JSONL Subprocess Runner Framework
All Untether engine runners (Claude, Codex, OpenCode, Pi; deprecated Gemini and AMP) extend JsonlSubprocessRunner, which manages subprocess lifecycle, JSONL parsing, session locking, and error handling.
Key files
| File | Purpose |
|---|---|
src/untether/runner.py |
JsonlSubprocessRunner base class, Runner protocol, SessionLockMixin, ResumeTokenMixin |
src/untether/model.py |
StartedEvent, ActionEvent, CompletedEvent, ResumeToken, Action, ActionKind |
src/untether/events.py |
EventFactory — consistent event creation per engine |
src/untether/backends.py |
EngineBackend dataclass, EngineConfig |
src/untether/progress.py |
ProgressTracker — aggregates actions for UI rendering |
src/untether/runner_bridge.py |
ProgressEdits, handle_message — connects runners to transport |
src/untether/runners/ |
Engine-specific runner implementations |
Class hierarchy
Runner (Protocol)
BaseRunner (SessionLockMixin)
JsonlSubprocessRunner
CodexRunner
OpenCodeRunner (wraps run_impl: refuses OpenCode 2.x before spawning, #970)
PiRunner
GeminiRunner, AmpRunner (deprecated, unsupported)
ClaudeRunner (overrides run_impl for PTY support)
(each concrete runner also mixes in ResumeTokenMixin)
Template methods to override
When creating a new runner, override these methods on JsonlSubprocessRunner:
class MyRunner(JsonlSubprocessRunner):
engine: EngineId = "myengine"
def command(self) -> str:
"""CLI binary name (e.g. 'codex', 'opencode', 'pi')."""
def build_args(self, prompt, resume, *, state) -> list[str]:
"""Build CLI arguments. Called once per run."""
def translate(self, data, *, state, resume, found_session) -> list[UntetherEvent]:
"""Translate a decoded JSON dict to Untether events. Core logic."""
def new_state(self, prompt, resume) -> Any:
"""Create per-run state (e.g. EventFactory, accumulators)."""
# Optional overrides:
def stdin_payload(self, prompt, resume, *, state) -> bytes | None:
"""Data to send on stdin. Default: prompt.encode()."""
def env(self, *, state) -> dict[str, str] | None:
"""Extra environment variables for the subprocess."""
def decode_jsonl(self, *, line: bytes) -> Any | None:
"""Custom JSON decoder. Default: json.loads."""
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.
- 18d ago Changed · +12 lines 549dc14557d8
- 1mo ago First seen · 243 lines · 52 tokens per session scan A a89176c6270b
jsonl-subprocess-runner is a skill published in the GitHub repository littlebearapps/untether (74 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 2,494 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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