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 skills add RayFernando1337/rayfernando-skills --skill wavesgit clone --depth 1 https://github.com/RayFernando1337/rayfernando-skillsWrote 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/rayfernando1337/rayfernando-skills/waves)<a href="https://agentmods.dev/skills/rayfernando1337/rayfernando-skills/waves"><img src="https://agentmods.dev/badge/skills/rayfernando1337/rayfernando-skills/waves.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00126 | $0.09169 |
| Opus 5 | $0.00063 | $0.04584 |
| Sonnet 5 | $0.00025 | $0.01834 |
| Haiku 4.5 | $0.00013 | $0.00917 |
Grade A, and why
waves scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
re-run/`curl`/validate served artifacts, regression-check sibling routes, and How it starts
The opening of the file, as written. The whole thing — 651 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WAVES — Workers · Aggregate · Verify · Extend (Cursor)
Run wave-based orchestration inside one local Cursor session. A wave is a
bounded round of isolated agents working in parallel, then a round that verifies
what came back, then a deliberate decision to build on it — not an open-ended
loop. You are the orchestrator: you discover, decompose the goal into
independent slices, fan them out to parallel workers (multiple Task tool
calls in one message, backgrounded where the surface supports it), read each
worker's structured handoff, verify it, and synthesize one deliverable.
Workers are isolated and return exactly one handoff.
The shape of every wave — WAVE:
- W — Workers. Fan out isolated workers across disjoint slices (the bounded parallel round).
- A — Aggregate. Wait for all of them and merge their structured handoffs at the synthesize barrier.
- V — Verify. The moat: check the evidence behind each handoff before you trust it.
- E — Extend. Decide — deliberately — whether to launch another wave, or stop.
A loop doesn't know when to stop; a wave does, because verification is the stop
function. (Invoked explicitly with /waves: a run spawns more agents than usual,
so it's opt-in, not auto-triggered.)
Waves runs in place of cloud orchestration. It adopts the principles the
Cursor team proved out in their cloud orchestrate plugin — planners plan,
workers hand off up, no cross-talk — but runs them on local subagents with zero
setup: no separate cloud agents, no API keys, no runtime. Local subagent runs
are the whole story here.
When to use
- A large goal that splits into independent slices (research areas, data chunks, files/modules, audit dimensions).
- The work is mostly read / research / analysis — the safest thing to parallelize locally (see "Parallel writes" for why).
- A single linear pass would be slow and you want real speedup from concurrency.
When to skip
- Small or linear tasks (just do them — fan-out overhead isn't worth it).
- Work needing tight back-and-forth or shared mutable state between steps.
- Parallel edits to the same files — local workers share one filesystem.
What ships with it
9 files 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.
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.
- 8d ago First seen · 651 lines · 126 tokens per session scan A 58791c720a2f
waves is a skill published in the GitHub repository RayFernando1337/rayfernando-skills (128 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 126 tokens to every session and 9,169 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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