Borrowing it
Nothing to install: this file belongs to jerseycheese/Narraitor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jerseycheese/Narraitor/main/.claude/skills/narraitor-parallel-lane-orchestration/SKILL.mdgit clone --depth 1 https://github.com/jerseycheese/NarraitorWrote 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/jerseycheese/narraitor/narraitor-parallel-lane-orchestration)<a href="https://agentmods.dev/skills/jerseycheese/narraitor/narraitor-parallel-lane-orchestration"><img src="https://agentmods.dev/badge/skills/jerseycheese/narraitor/narraitor-parallel-lane-orchestration/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.
<a href="https://agentmods.dev/skills/jerseycheese/narraitor/narraitor-parallel-lane-orchestration"><img src="https://agentmods.dev/badge/skills/jerseycheese/narraitor/narraitor-parallel-lane-orchestration.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00130 | $0.02511 |
| Opus 5.5 | $0.00052 | $0.01004 |
| Sonnet 5.5 | $0.00026 | $0.00502 |
| Haiku 4.5 | $0.00013 | $0.00251 |
Grade A, and why
narraitor-parallel-lane-orchestration 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 28d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel lane orchestration (Fable orchestrator, tiered lane agents)
1. What this is
One Fable-model session acts as orchestrator. It picks N issues off the backlog, pre-builds a
git worktree per issue, and spawns one Agent-tool subagent per lane — each lane's model chosen
from that issue's model-power:* label, so cheap work runs cheap. The orchestrator never
implements; it selects, partitions, dispatches, unblocks, and reports.
The mechanism that works here is the in-harness Agent tool, not claude -p children
(host-held OAuth 401s) and not a paste-block of terminal commands.
2. When to use
For a whole milestone (intake, shaping, batches of issues per PR, Codex or Gemini lanes, cloud vs local,
the release), use narraitor-backlog-routing instead. It builds on this skill, and §6 below stays the
canonical trap list for both.
- "Work the next N most important issues in parallel."
- A backlog push where serial execution would waste hours of wall clock.
- Any time a batch is big enough that batch selection is itself a real decision.
Do not use for a single issue (ship-issue / tdd-implement are cheaper), or when the batch
would all touch the same file (see collision rules — that batch is serial by nature).
3. Model tiering
model-power:* is the delegation axis (complexity:* is time/scope, not reasoning difficulty).
Definitions live in .github/labels.md.
| Label | Lane model |
|---|---|
model-power:light |
haiku |
model-power:standard |
sonnet |
model-power:advanced |
opus |
model-power:frontier |
keep out of the batch, or run it in the orchestrator session |
An unlabeled issue is not automatically standard — read the body and assign a tier, saying so.
The labels were applied in a single retroactive pass, so treat a tier that fights the body as
wrong and score the body.
4. Batch selection
Run the prioritize-issues skill for the ranking, then subtract everything that cannot safely
run right now. That skill is user-level, not committed here — where it isn't available (a fresh
clone, a cloud session), the repo ships .claude/agents/issue-prioritizer.md, which does the
same ranking job:
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.
- 28d ago Changed · +5 lines 9c544523827e
- 2mo ago First seen · 175 lines · 130 tokens per session scan A f97d6752e2d9
narraitor-parallel-lane-orchestration is a skill published in the GitHub repository jerseycheese/Narraitor (32 stars, last pushed 4d ago), licensed MIT. It adds 130 tokens to every session and 2,511 once invoked, about $0.0005 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.
Other skills, from other repositories
merge-batch
Prepare and merge an owner-selected PR batch with contributor credit and exact-candidate admission. Use for a pasted PR list; combined focused validation is diagnostic, and every actual landing still requires its applicable checks and authorization.
prowler-commit
Creates professional git commits following conventional-commits format. Trigger: When creating commits, after completing code changes, when user asks to commit.
gh-auth-isolation
Safely manage multiple GitHub identities (EMU + personal) in agent workflows.
comet-github
A routing guide for Comet-related GitHub work. It directs requests about pull requests, issues, CI failures, ideas, and fixes to the appropriate review or implementation process.
github-skill
Work with GitHub via the gh CLI — clone repositories, create/list/merge pull requests, create/list issues, and run any other gh command (API calls, workflow runs, releases, repo administration). List operations return parsed JSON.
release-helper
Ensures configuration and code changes are released correctly. Use PROACTIVELY whenever you edit config.json, change any setting, or fix a configuration bug in this project, so the change reaches production.