agent-wave

A workflow that assigns items from a software project’s plan or to-do queue to several coding agents working in parallel.

In plain words
What is it for?
Use it to run implementation work in waves, choose how many agents and items to use, collect their results, and coordinate changes across worktrees.
Why use it?
It helps process independent work items at the same time while accounting for shared files, isolated work areas, budgets, and progress checkpoints.

Skill for Claude CodeCodex

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 skills/evolvehq/docflow/agent-wave
Any agent
npx skills add EvolveHQ/docflow --skill agent-wave
Clone the repo
git clone --depth 1 https://github.com/EvolveHQ/docflow

Made for: Claude Code, Codex.

Per session 105 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,824 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 $0.00105 $0.01824
Opus 5 $0.00053 $0.00912
Sonnet 5 $0.00021 $0.00365
Haiku 4.5 $0.00011 $0.00182

Measured 2d ago against content hash ec1fd84059ea, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-wave 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.

plugins/docflow/skills/agent-wave/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

agent-wave

Drive the implementation queue with parallel subagents, in waves.

Honest scope (read first)

In-session subagents are bounded by this session, not by wall-clock hours. So this skill measures budget reliably in items and waves, with hours as a soft cap (stop starting new waves once elapsed time passes it). For a true multi-hour unsupervised fleet that outlives a session, use remote agents or a scheduled run of _agent/prompts/autonomous.md (/schedule) instead — this skill points you there rather than pretending to be it.

Step 0 — Preconditions and context

  1. Confirm the repo is bootstrapped with a plan/ queue and that _agent/prompts/autonomous.md exists (a real verify gate is required — see the bootstrap skill, Q8).
  2. Read CONVENTIONS.md for the multi-agent mode and integration model.
    • Mode 1 (single agent): refuse. Parallel agents in one checkout clobber each other. Tell the user to re-bootstrap as mode 2/3, or run the autonomous prompt sequentially instead.
    • Mode 2 (shared checkout): allowed but warn — file contention is real; LOCKS must be respected and wave width kept low.
    • Mode 3 (worktrees): the intended mode. Each subagent works in its own isolated worktree.

Step 0.5 — Assessment (run first)

Run the shared assessment protocol before spawning anything:

  • Depth selector first. Ask how deep this assessment should go: express — every choice takes its recommended default; only questions with no derivable default (the free-text essentials) are still asked; guided — only the questions marked high-impact below, plus the free-text essentials; full — every question below. If the repo's CONVENTIONS.md records an Assessment depth:, pre-select it as the recommended option — the selector always appears; a recorded depth is never applied silently. Otherwise recommend full when the request arrived with little or no context and express when it is already fully specified. At any question the operator may answer "defaults from here" or "go deeper"; honour the switch immediately.

Read the full file on GitHub · 146 lines

Files

What ships with it

1 file 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.

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 · 146 lines · 105 tokens per session scan A ec1fd84059ea

Subscribe to this mod's changes

agent-wave is a skill published in the GitHub repository EvolveHQ/docflow (10 stars, last pushed 27d ago), licensed MIT. It adds 105 tokens to every session and 1,824 once invoked, about $0.0005 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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