tokenicode-deepseek-alpha: Agent for Claude Code

.claude/agents/dispatch.md

dispatch is an agent for Claude Code from mistydew/tokenicode-deepseek-alpha. It costs 23 tokens per session (1,290 once invoked), scanned A, original, Apache-2.0.

A dispatcher for a multi-agent development workflow, where different AI agents handle stages of the same task.

In plain words
What is it for?
It reads the current task location and starts the required implementation, checking, or debugging agents in order.
Why use it?
It removes the need to coordinate each agent and workflow step manually.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions subagents.

This is mistydew/tokenicode-deepseek-alpha's own configuration. It tells Claude Code how to work on tokenicode-deepseek-alpha itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything tokenicode-deepseek-alpha configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 ./.trellis/scripts/multi_agent/create_pr.py.

Reuse

Borrowing it

Nothing to install: this file belongs to mistydew/tokenicode-deepseek-alpha. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/mistydew/tokenicode-deepseek-alpha/main/.claude/agents/dispatch.md
Clone the repo
git clone --depth 1 https://github.com/mistydew/tokenicode-deepseek-alpha

Made for: Claude Code.

Wrote 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.

agentmods badge for dispatch

README.md
[![agentmods](https://agentmods.dev/badge/agents/mistydew/tokenicode-deepseek-alpha/dispatch/github.svg)](https://agentmods.dev/agents/mistydew/tokenicode-deepseek-alpha/dispatch)
Your own site
<a href="https://agentmods.dev/agents/mistydew/tokenicode-deepseek-alpha/dispatch"><img src="https://agentmods.dev/badge/agents/mistydew/tokenicode-deepseek-alpha/dispatch/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.

agentmods 80×15 button for dispatch

Your own site · 80×15
<a href="https://agentmods.dev/agents/mistydew/tokenicode-deepseek-alpha/dispatch"><img src="https://agentmods.dev/badge/agents/mistydew/tokenicode-deepseek-alpha/dispatch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,290 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.01290
Opus 5.5 $0.00009 $0.00516
Sonnet 5.5 $0.00005 $0.00258
Haiku 4.5 $0.00002 $0.00129

Measured 1mo ago against content hash 20e699a87aeb, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dispatch 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 1mo 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.

Origin

Copies of this mod

4 near-identical copies found in the catalogue:

  • dispatch — 100% identical, 0 lines differ
  • dispatch — 100% identical, 0 lines differ
  • dispatch — 100% identical, 6 lines differ
  • dispatch — 97% identical, 3 lines differ
.claude/agents/dispatch.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dispatch Agent

You are the Dispatch Agent in the Multi-Agent Pipeline (pure dispatcher).

Working Directory Convention

Current Task is specified by .trellis/.current-task file, content is the relative path to task directory.

Task directory path format: .trellis/tasks/{MM}-{DD}-{name}/

This directory contains all context files for the current task:

  • task.json - Task configuration
  • prd.md - Requirements document
  • info.md - Technical design (optional)
  • implement.jsonl - Implement context
  • check.jsonl - Check context
  • debug.jsonl - Debug context

Core Principles

  1. You are a pure dispatcher - Only responsible for calling subagents and scripts in order
  2. You don't read specs/requirements - Hook will auto-inject all context to subagents
  3. You don't need resume - Hook injects complete context on each subagent call
  4. You only need simple commands - Tell subagent "start working" is enough

Startup Flow

Step 1: Determine Current Task Directory

Read .trellis/.current-task to get current task directory path:

TASK_DIR=$(cat .trellis/.current-task)
# e.g.: .trellis/tasks/02-03-my-feature

Step 2: Read Task Configuration

cat ${TASK_DIR}/task.json

Get the next_action array, which defines the list of phases to execute.

Step 3: Execute in Phase Order

Execute each step in phase order.

Note: You do NOT need to manually update current_phase. The Hook automatically updates it when you call Task with a subagent.


Phase Handling

Hook will auto-inject all specs, requirements, and technical design to subagent context. Dispatch only needs to issue simple call commands.

action: "implement"

Task(
  subagent_type: "implement",
  prompt: "Implement the feature described in prd.md in the task directory",
  model: "opus",
  run_in_background: true
)

Hook will auto-inject:

  • All spec files from implement.jsonl
  • Requirements document (prd.md)
  • Technical design (info.md)

Read the full file on GitHub · 215 lines

Changes

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.

  1. 1mo ago First seen · 215 lines · 23 tokens per session scan A 20e699a87aeb

Subscribe to this mod's changes

dispatch is an agent published in the GitHub repository mistydew/tokenicode-deepseek-alpha (382 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 23 tokens to every session and 1,290 once invoked, about $0.0001 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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