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/deepgram/wsh/agent-orchestrationnpx skills add deepgram/wsh --skill agent-orchestrationgit clone --depth 1 https://github.com/deepgram/wshWrote 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/deepgram/wsh/agent-orchestration)<a href="https://agentmods.dev/skills/deepgram/wsh/agent-orchestration"><img src="https://agentmods.dev/badge/skills/deepgram/wsh/agent-orchestration.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 | $0.00078 | $0.02317 |
| Opus 5 | $0.00039 | $0.01158 |
| Sonnet 5 | $0.00016 | $0.00463 |
| Haiku 4.5 | $0.00008 | $0.00232 |
Grade C, and why
agent-orchestration scanned grade C with 2 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 4d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
# See: "Run command: rm -rf /tmp/build" Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> 2. **If you do NOT have `wsh_*` tools**: you are in HTTP/curl fallback mode. How it starts
The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IMPORTANT: EXECUTION CONTEXT This skill describes what to do — domain patterns and decision-making. It does NOT describe how to call the API.
- If you have
wsh_*tools (check your toolkit forwsh_send_input,wsh_get_screen, etc.): use them directly. Operation names in this skill generally map to tool names (e.g., "send input" →wsh_send_input). When in doubt, list your availablewsh_*tools.- If you do NOT have
wsh_*tools: you are in HTTP/curl fallback mode. DO NOT GUESS endpoints or CLI subcommands. Load the full API reference first: search your workspace forskills/core/and readSKILL.md. It contains every endpoint with working curl examples and a bootstrap sequence.- Quick bootstrap:
curl -sf --unix-socket ${XDG_RUNTIME_DIR:-/tmp}/wsh/default.http.sock http://localhost/health— if that fails:wsh server -L agent-$$ --ephemeral &and retry.
wsh:agent-orchestration — Driving AI Agents
You can use wsh to launch and drive other AI agents — Claude Code, Aider, Codex, or any AI tool with a terminal interface. This is not science fiction. You spawn the agent in a wsh session, feed it tasks, handle its approval prompts, and review its output. You become a manager of AI workers.
Why?
- Parallelism. You can run 5 Claude Code sessions simultaneously, each working on a different task.
- Delegation. Break a large project into subtasks and assign each to an agent session.
- Specialization. Different agents have different strengths. Orchestrate the right tool for each job.
- Automation. Unattended workflows — an agent that spawns agents, reviews their work, and merges the results.
Launching an Agent
Create a session with the agent as its command:
create session "agent-auth" with command: claude --print "Implement user auth in src/auth.rs"
Or start a shell and launch the agent interactively:
create session "agent-auth"
send: claude
wait for idle
read screen — verify Claude Code has started
send: Implement user authentication in src/auth.rs\n
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.
- 4d ago First seen · 293 lines · 78 tokens per session scan C 1dc54145d5ef
agent-orchestration is a skill published in the GitHub repository deepgram/wsh (5 stars, last pushed 3mo ago), licensed ISC. It adds 78 tokens to every session and 2,317 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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