do

A request-routing command that classifies a task and selects the appropriate agent and skill to handle it. It can also add relevant project knowledge and reviewers before execution.

In plain words
What is it for?
Use it to route implementation and other project requests to suitable agents and skills, including more complex work that benefits from parallel review.
Why use it?
It reduces the need to decide manually which specialized workflow fits a request. The selected workflow is then planned and dispatched for execution.

Command

Install

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.

agentmods
npx agentmods add commands/notque/vexjoy-agent/do
Clone the repo
git clone --depth 1 https://github.com/notque/vexjoy-agent
Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 346 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00013 $0.00346
Opus 5 $0.00006 $0.00173
Sonnet 5 $0.00003 $0.00069
Haiku 4.5 $0.00001 $0.00035

Measured 2d ago against content hash 4fcad962fc0b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

do 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.

commands/do.md · 44 lines

What it actually says

/do - Smart Router

Route user requests to the correct agent + skill combination.

Instructions

Call the Skill tool with do. Follow its classification, routing, enhancement, and execution phases.

Base directory: $CLAUDE_PROJECT_DIR or the current working directory
Skill file: skills/meta/do/SKILL.md

Phase 1: CLASSIFY — Assess complexity, check parallel patterns Phase 2: ROUTE — Select agent + skill, display routing banner Phase 3: ENHANCE — Stack retro knowledge, anti-rationalization, parallel reviewers Phase 4: EXECUTE — Create the plan and dispatch through build-dispatch.py. The builder emits Call the Skill tool with \skill-name`.` once for the primary skill and each callable stack skill.

Learning capture runs automatically via hooks — no router step (see "Learning Capture" in the skill).

The routing banner MUST be the first visible output:

===================================================================
 ROUTING: [brief summary]
===================================================================

 Selected:
   -> Agent: [name]
   -> Skill: [name]

 Invoking...
===================================================================

For complete routing, force-route triggers, and domain agent mappings, read skills/meta/do/SKILL.md; the routing manifest is generated by scripts/routing-manifest.py from the INDEX files (single source of truth).

ARGUMENTS: $ARGUMENTS

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. 2d ago First seen · 44 lines · 13 tokens per session scan A 4fcad962fc0b

Subscribe to this mod's changes

do is a command published in the GitHub repository notque/vexjoy-agent (417 stars, last pushed 2d ago), licensed MIT. It adds 13 tokens to every session and 346 once invoked, about $0.0001 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 2026-08-30.