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/letta-ai/letta-code/dispatching-coding-agentsnpx skills add letta-ai/letta-code --skill dispatching-coding-agentsgit clone --depth 1 https://github.com/letta-ai/letta-codeWhat 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 | $0.00000 | $0.02915 |
| Opus 5 | $0.00000 | $0.01458 |
| Sonnet 5 | $0.00000 | $0.00583 |
| Haiku 4.5 | $0.00000 | $0.00292 |
Grade A, and why
dispatching-coding-agents 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 2d 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dispatching Coding Agents
You can shell out to Claude Code (claude) and Codex (codex) as stateless sub-agents via Bash. They have filesystem and tool access (scope depends on sandbox/approval settings) but zero memory — every session starts from scratch.
Default to run_in_background: true on the Bash call so you can keep working while they run. Check results later with TaskOutput. Don't sit idle waiting for a subagent.
The Core Mental Model
Claude Code and Codex are highly optimized coding agents, but are re-born with each new session. Think of them like a brilliant intern that showed up today. Provide them with the right instructions and context to help them succeed and avoid having to re-learn things that you've learned.
You are the experienced manager with persistent memory of the user's preferences, the codebase, past decisions, and hard-won lessons. Give them context, not a plan. They won't know anything you don't tell them:
- Specific task: Be precise about what you need — not "look into the auth system" but "trace the request flow from the messages endpoint through to the LLM call, cite files and line numbers."
- File paths and architecture: Tell them exactly where to look and how pieces connect. They will wander aimlessly without this.
- Preferences and constraints: Code style, error handling patterns, things the user has corrected you on. Save them from making mistakes you already learned from.
- What you've already tried: If you're dispatching because you're stuck, this prevents them from rediscovering your dead ends.
If a subagent needs clarification or asks a question, respond in the same session (see Session Resumption below) — don't start a new session or you'll lose the conversation context.
When to Dispatch (and When Not To)
Dispatch for:
- Hard debugging — you've been looping on a problem and need fresh eyes
- Second opinions — you want validation before a risky change
- Parallel research — investigate multiple hypotheses simultaneously
- Large-scope investigation — tracing a flow across many files in an unfamiliar area
- Code review — have another agent review your diff or plan
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.
- 2d ago First seen · 233 lines · 0 tokens per session scan A 477fb6d99c37
dispatching-coding-agents is a skill published in the GitHub repository letta-ai/letta-code (3,178 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,915 tokens. 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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