Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ericrisco/rsc-harnessnpx agentmods add skills/ericrisco/rsc-harness/parallelWrote 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/ericrisco/rsc-harness/parallel)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/parallel"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/parallel.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 | $0.00080 | $0.03399 |
| Opus 5 | $0.00040 | $0.01699 |
| Sonnet 5 | $0.00016 | $0.00680 |
| Haiku 4.5 | $0.00008 | $0.00340 |
Grade A, and why
parallel 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 4d 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
parallel — fan out independent work, then reconcile
Parallelism is a property of the work, not a wish. Prove the pieces are disjoint, dispatch one subagent per piece with a self-contained brief, then gather and reconcile before anyone calls it done.
This is an on-demand process skill in the SDD chain. You reach it from implement (or any phase) when the work in front of you splits into pieces that could each be handed to a different person who never talks to the others. It owns one discipline: partition → dispatch → gather → reconcile. It does not own the work inside each piece — a subagent building a module still runs its own red → green → refactor loop from implement; this skill only orchestrates the fan-out. It also does not own the place the work runs: a clean branch or checkout to work in is worktrees. parallel decides what can run at the same time; worktrees provides the isolation it runs in.
The whole value is in the gate at the front. Run work in parallel only when it is actually independent. Forcing parallelism onto coupled work does not make it faster — it makes it a merge disaster, and the time you save dispatching you lose tenfold reconciling. Most of this skill is about earning the right to parallelize.
The independence test (run this before dispatching anything)
A set of tasks is safe to parallelize only when every answer below is yes. One no means serialize that pair.
INDEPENDENCE TEST — for every PAIR of candidate tasks
- [ ] Disjoint files — they never write the same file (and don't both edit a shared barrel/index/registry)
- [ ] No shared state — no shared in-memory object, DB row, migration, global config, or env they both mutate
- [ ] No ordering edge — neither needs the other's OUTPUT to start or to assert against
- [ ] No hidden coupling — not the same schema/contract/type that must agree, not the same external resource
- [ ] Self-containable brief — each can be described fully on its own, with its own done-check, without "see the other task"
What ships with it
2 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.
- 4d ago First seen · 169 lines · 80 tokens per session scan A 48c56222a354
parallel is a skill published in the GitHub repository ericrisco/rsc-harness (70 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 3,399 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
batch
Execute batch operations on multiple files in parallel. Automatically discovers files, splits into chunks, and processes with parallel worker agents. Use /batch followed by operation and file pattern.
loop
Create a loop that runs a prompt now and follows up either on a fixed schedule or through self-paced wakeups. Usage - /loop check the build, /loop 5m check the build, /loop check the PR every 30m. /loop list to show jobs, /loop clear to cancel all.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
agf
Find local coding-agent sessions, inspect bounded metadata or summaries, and prepare a read-only resume plan with AGF. Use for finding prior work across agent CLIs, not for executing agents, deleting sessions, or reading full transcripts.
openrig-herdr
Use when opening OpenRig fleet terminals as a herdr wall — turning a rig, pod, mission, slice, or saved view into live interactive agent tiles via rig terminal, watching another rig read-only, or driving herdr on an agent's request ("open all my rigs + a mission as views"). Covers the rig terminal open|views|status…
neosh
Run and manage long-lived coding agents in a neosh workspace from the command line — start conversations in any directory or git worktree, fan work out across many at once, watch and steer them while they run, read what they produced, and clean up. Use whenever the user asks to delegate work to neosh, run something…