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 sakurameishi/codex-dsh-mcp --skill dsh-batch-subagentsgit clone --depth 1 https://github.com/sakurameishi/codex-dsh-mcpWrote 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/sakurameishi/codex-dsh-mcp/dsh-batch-subagents)<a href="https://agentmods.dev/skills/sakurameishi/codex-dsh-mcp/dsh-batch-subagents"><img src="https://agentmods.dev/badge/skills/sakurameishi/codex-dsh-mcp/dsh-batch-subagents/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/sakurameishi/codex-dsh-mcp/dsh-batch-subagents"><img src="https://agentmods.dev/badge/skills/sakurameishi/codex-dsh-mcp/dsh-batch-subagents.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 | $0.00076 | $0.01237 |
| Opus 5 | $0.00038 | $0.00619 |
| Sonnet 5 | $0.00015 | $0.00247 |
| Haiku 4.5 | $0.00008 | $0.00124 |
Grade A, and why
dsh-batch-subagents 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 11d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DSH Batch Subagents
Use the bundled scripts/dsh-batch-agents.mjs controller. Resolve the script path relative to this SKILL.md and invoke it with node.
Operating contract
- Keep Codex as the commander and final reviewer. DSH workers may inspect, edit, and test only inside their isolated worktrees.
- Never merge, cherry-pick, or apply a worker patch to the main workspace automatically. Review the Markdown report and patch first, then make approved changes through the normal Codex editing workflow.
- Prefer independent, bounded tasks with explicit deliverables. Avoid giving multiple workers overlapping implementation ownership.
- The controller serializes headless execution for workers sharing one
DSH_HOME, including workers from separate runs, because current DSH profiles share mutable startup state. On Windows it also clamps each batch to one active worker. A batch may still contain many independent tasks; they wait durably for the shared profile slot. - A Git repository with a valid
HEADis required. If the current folder is not one, locate the intended nested repository or ask the user which repository to use. Do not silently snapshot a large non-Git directory. - Worktrees are based on committed
HEAD; uncommitted main-workspace changes are not copied. Surface the dirty-worktree warning from the report before judging results. - Keep run artifacts until the user has reviewed them.
cleanupremoves only isolated worktrees and preserves reports and patches.
Duration-aware execution
Estimate a duration range before launching every DSH task or batch. Use the scope, prior similar runs, or a small representative check as the basis, and tell the user the estimate before launch.
- 10 minutes or less: Keep the work in the current turn. Use
--foregroundonly when synchronous completion is useful, follow yielded execution with bounded waits, and give concise progress updates at least every 60 seconds. - More than 10 minutes, or a range crossing 10 minutes: Launch without
--foregroundso the controller remains durable. Record the run directory, task IDs, start time, estimate range, and next check near the lower end of the expected completion window. End the active turn after launch unless useful independent work remains. - Always pass a real controller deadline with
--task-timeout-seconds. The deadline covers worktree preparation, waiting for the shared DSH profile lock, and agent execution. - At the scheduled check, read
status --jsonfirst. If state has not changed, do not open logs or emit repeated updates. ReadREVIEW.md, reports, patches, and log tails only for completion, failure, stale state, or a meaningful checkpoint. - Never create a tight
wait/statuspolling loop for a long batch. If recurring monitoring is explicitly requested or the estimate is highly uncertain, use one monitor at an appropriate interval rather than keeping the active turn open. - Treat unchanged external state as normal. A running task is not blocked or failed merely because it exceeded a conversational turn.
What ships with it
2 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.
- 11d ago First seen · 67 lines · 76 tokens per session scan A 660d173c8f21
dsh-batch-subagents is a skill published in the GitHub repository sakurameishi/codex-dsh-mcp (0 stars, last pushed 13d ago), licensed MIT. It adds 76 tokens to every session and 1,237 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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