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 agentprism/agentprism-workflows --skill agentprism-repl-orchestrationgit clone --depth 1 https://github.com/agentprism/agentprism-workflowsWrote 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/agentprism/agentprism-workflows/agentprism-repl-orchestration)<a href="https://agentmods.dev/skills/agentprism/agentprism-workflows/agentprism-repl-orchestration"><img src="https://agentmods.dev/badge/skills/agentprism/agentprism-workflows/agentprism-repl-orchestration/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/agentprism/agentprism-workflows/agentprism-repl-orchestration"><img src="https://agentmods.dev/badge/skills/agentprism/agentprism-workflows/agentprism-repl-orchestration.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 | $0.00056 | $0.00924 |
| Opus 5 | $0.00028 | $0.00462 |
| Sonnet 5 | $0.00011 | $0.00185 |
| Haiku 4.5 | $0.00006 | $0.00092 |
Grade A, and why
agentprism-repl-orchestration 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 3d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REPL orchestration: quickstart
Context: JavaScript sent to the MCP repl tool. This is not workflow-script code: REPL agent() takes (modelSpec, task, options?), top-level return is a syntax error, and named bindings persist between calls.
The REPL is one persistent QuickJS-in-WASM workspace per absolute projectDir. Use it when you want to inspect intermediate results and decide the next step interactively. Use workflow when the full orchestration is known up front and should be repeatable as one deterministic script.
First eval
const audit = agent("codex", "Inspect the parser for correctness bugs");
Send that code using:
{ "action": "eval", "projectDir": "/absolute/project", "code": "..." }
agent() returns a persistent promise-handle immediately. Storing the handle before awaiting preserves its id, queue(), steer(), and cancel() methods for later evals.
Inspect or await it in another eval:
agents()
const report = await audit;
report
A completed eval returns { output, result? }. If the soft hold bound expires while the eval remains suspended, the tool returns { output, running: [callIds] }; execution continues server-side. Poll without running new code by evaluating the empty string:
{ "action": "eval", "projectDir": "/absolute/project", "code": "" }
Essential semantics
- Top-level
awaitworks; top-levelreturndoes not. let,const,var, functions, and classes remain available to later evals._is the previous eval's completion value.- Console output is returned as text but is not a persistent value. Assign values you need later.
- There is no filesystem, network, import, or general timer API in the VM. Subagents perform external work;
sleep(ms)is the one host-backed timer. - The default eval hold is 60 seconds and the per-call maximum is 120 seconds. This is a response hold, not cancellation.
- Use
interruptwith a callidto cancel one subagent/queued turn, or omitidto break the currently running eval. workspace()shows bindings, in-flight calls, checkpoints, and diagnostics.agents()shows live agent lanes and queued turns.reset()tears the workspace down after the current eval completes.
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.
- 3d ago First seen · 84 lines · 56 tokens per session scan A 45156e0c239c
agentprism-repl-orchestration is a skill published in the GitHub repository agentprism/agentprism-workflows (6 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 924 once invoked, about $0.0003 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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