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Get Started Free →Configure delegation fleet lanes: which implementer CLI handles which kind of work, with optional model and effort (or variant) dials. Discovers installed CLIs, proposes a lane map for user approval, and writes global or project config only after explicit yes. Use when the user asks to set up, configure, or reconfigure delegation lanes, a fleet of lanes, or which implementer handles feature/tests/ui work — not for dispatching a coding task to an implementer.
.claude/skills/amelnagdy-delegate-setup/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 76% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 18% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 80% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 138% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 150% | 0% |
You are the orchestrator in setup mode. Discover installed implementer CLIs, propose a fleet of lanes, and write configuration only after the user approves.
This skill does not dispatch coding work. It only authors the lane map.
One concept: lanes. Never say “routes.”
Example lane: feature → implementer opencode, model opencode/grok, variant high (OpenCode uses variant for reasoning intensity, not effort).
*-delegate skill instead.--model / --effort / --variant on that relay.implementer.model, effort or variant, …) only if that implementer supports them — see references/schema.md.AGENTS.md, CLAUDE.md, or other user agent-instruction files.*-delegate relay from this skill.(<skill-dir> is this skill’s install directory — the folder that contains this SKILL.md.)
discover → load → grounding menu → propose (with Basis) → scope → approve → write
bashnode "<skill-dir>/scripts/discover.mjs"
Summarize installed vs missing, auth (true / false / null = unknown), and whether models were reported, aliases (curated aliases in the registry, not live discovery — full model names also work), unsupported, or failed.
bashnode "<skill-dir>/scripts/config.mjs" load --cwd "$PWD"
global / project). Do not pasteboth raw files unless asked.
projectPresent is true and projectTrusted is false, label the project lanes untrusted.They cannot dispatch until the user reviews and approves a project write.
Discovery reports capability, never task fit. So ask one grounding question before proposing anything — one question, three options, not a wizard:
> How should I pick the lanes? (1) Quick defaults — I decide, no questions. > (2) Interview — about four questions on how you want work allocated. > (3) Usage scan — I re-read your CLIs’ local session folders (counts and dates only, never the > conversations) and let the numbers place your lanes — if one CLI dominates, expect one question > about its role. Happy to do 2 and 3 together.
(one medium per round) live in references/setup-dialogue.md — read it before you ask.
node "<skill-dir>/scripts/discover.mjs" --usage. Tell the user it is metadataonly before running it. Each discovered CLI gains usage: { sessions, lastUsed }; null means no probe is wired — unknown, not unused.
evidence. They do not change the menu; they feed the proposal and the repo basis.
That menu is also the consent surface — the option chosen sets how much of the map is yours to decide:
every lane my opinion, say plainly that the map is your opinion, and keep it cheap to revise.
the user’s answer, or where the schema requires it (opencode lanes require model). Omitting is always safe — every dial has a default the user already lives with, and a CLI’s configured default is their standing choice, better evidence than your priors. Choosing which installed implementer gets a lane is still yours — Basis my opinion — but a dial that raises spend is not: offer your dial picks only as an addendum after the proposal, see references/setup-dialogue.md.
conservative lanes, name the axis you are blind on (no quota answer → say the map is quota-blind), and invite the answer anytime. Re-ask once at most; never backfill silence with priors.
Delegation economics. The orchestrator reviews and lands every result — the review is the quality gate, so optimize total cost, not implementer prestige:
(tests, mechanical refactors, straightforward fixes) when their reliability keeps review and rework economical — lanes push token burn away from the subscriptions the user is protecting. Low usage alone does not establish burnable: discovery cannot see plans, limits, or per-run cost, and a rarely-used CLI may be metered or deliberately avoided. Burnable comes from the user's quota answer — or, in quick defaults, from your labeled opinion.
only when the user asks for it or no acceptable alternative exists. Lanes are orchestrator-blind: the same lane fires from every seat the user drives from, and from that CLI's own seat it dispatches the CLI to itself.
implementer is flaky; when correctness rides on security, concurrency, migrations, or unstated domain knowledge; and when the output is the product (debate, architecture, research) — review limits damage, it does not manufacture a good first attempt. Bind those lanes to stronger implementers.
posture answers on any lane the user explicitly retains for X — ask whether the posture applies there; omit the dial if unanswered. Never silently stretch one answer across an axis it conflicts with.
Question phrasings for the burn/spare and trust interview live in references/setup-dialogue.md.
Then propose the lanes. Name them after the work the user described; fall back to feature, tests, ui, fast, complex. Installed implementers only.
Show:
| Lane | Implementer | Model | Effort / variant | Basis | Source (if updating) | | --- | --- | --- | --- | --- | --- | | feature | opencode | opencode/grok | variant: high | your answer + schema requirement | — | | tests | codex | — | — | usage data | — | | ui | claude | — | — | my opinion (implementer) | — |
Basis is mandatory on every lane: your answer / usage data / repo / my opinion / schema requirement (a dial the schema forces is neither evidence nor opinion — say so). A lane you picked from model-quality priors is my opinion — never present it as something the tooling determined, and “installed and authenticated” is capability, not evidence of fit. When a lane’s implementer and its dials come from different places, split the label — see references/setup-dialogue.md.
Then the complete JSON (version: delegate-fleet.v1). One line of why per lane; flag auth or model uncertainty.
Schema and dial table: references/schema.md.
global.global (say so).On explicit yes, write only the chosen scope (validate first). Build the payload from that scope’s raw file (or an empty lanes object if new) — not from the effective merged load view, or a project write will shadow global-only lanes and a global write will promote project-only ones.
Create a uniquely named file under the platform temporary directory ($TMPDIR, %TEMP%, or Node os.tmpdir(); never hard-code /tmp, which breaks on native Windows), write the exact approved JSON into it with the orchestrator's file-writing tool, and use that populated path as <lanes-json> below. Never validate an empty temp file. Remove the temp file after the validation/write attempt, whether it succeeds or fails.
bashnode "<skill-dir>/scripts/config.mjs" validate "<lanes-json>" node "<skill-dir>/scripts/config.mjs" write --scope global "<lanes-json>" # or: write --scope project --cwd /path/to/repo "<lanes-json>"
Re-read with load, then confirm the path written and the active lane names. Project writes bind approval to the exact config content; later changes fail closed until re-approved. On update, a short before/after is enough.
Stop after confirming. Tell the user the map is ready. For later work: read the lane’s implementer, load that *-delegate skill, and dispatch with --lane <name> (explicit --model / --effort / --variant still win when passed). Do not start a delegate task unless they ask.
Same flow. Show the effective current map, propose changes, approve, write one scope’s file. Reinstalling the skills package must not rewrite these files — they live outside the package.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 21,341 | 17,719 | -17% | 1 | 1 | 0% | 615 | 2,970 | +383% | 0 | 0 | — |
case-02 | fail→fail | 17,153 | 12,214 | -29% | 1 | 1 | 0% | 503 | 2,954 | +487% | 0 | 0 | — |
case-03 | fail→fail | 34,405 | 13,783 | -60% | 1 | 1 | 0% | 2,780 | 3,080 | +11% | 0 | 0 | — |
case-04 | fail→fail | 22,768 | 12,292 | -46% | 1 | 1 | 0% | 2,420 | 2,855 | +18% | 0 | 0 | — |
case-05 | fail→fail | 16,115 | 6,967 | -57% | 1 | 1 | 0% | 1,929 | 2,866 | +49% | 0 | 0 | — |
case-06 | fail→fail | 13,501 | 21,504 | +59% | 1 | 1 | 0% | 1,161 | 3,124 | +169% | 0 | 0 | — |
case-07 | fail→pass | 14,540 | 12,135 | -17% | 1 | 1 | 0% | 1,867 | 3,286 | +76% | 0 | 0 | — |
case-08 | fail→fail | 15,171 | 18,327 | +21% | 1 | 1 | 0% | 2,426 | 3,723 | +53% | 0 | 0 | — |
case-09 | pass→pass | 9,919 | 5,212 | -47% | 1 | 1 | 0% | 1,357 | 3,291 | +143% | 0 | 0 | — |
case-10 | fail→pass | 17,340 | 8,172 | -53% | 1 | 1 | 0% | 3,174 | 3,749 | +18% | 0 | 0 | — |
case-11 | fail→pass | 13,228 | 7,893 | -40% | 1 | 1 | 0% | 1,711 | 3,083 | +80% | 0 | 0 | — |
case-12 | pass→pass | 9,028 | 4,188 | -54% | 1 | 1 | 0% | 1,306 | 3,232 | +147% | 0 | 0 | — |
case-13 | fail→pass | 14,058 | 8,333 | -41% | 1 | 1 | 0% | 1,311 | 3,124 | +138% | 0 | 0 | — |
case-14 | fail→fail | 19,056 | 15,778 | -17% | 1 | 1 | 0% | 2,505 | 2,785 | +11% | 0 | 0 | — |
case-15 | pass→pass | 11,980 | 12,471 | +4% | 1 | 1 | 0% | 1,739 | 3,740 | +115% | 0 | 0 | — |
case-16 | pass→fail | 13,574 | 14,001 | +3% | 1 | 1 | 0% | 1,418 | 3,301 | +133% | 0 | 0 | — |
case-17 | fail→pass | 7,769 | 3,270 | -58% | 1 | 1 | 0% | 1,261 | 3,154 | +150% | 0 | 0 | — |
case-18 | fail→pass | 10,284 | 12,937 | +26% | 1 | 1 | 0% | 310 | 3,689 | +1090% | 0 | 0 | — |
case-19 | pass→fail | 8,459 | 13,274 | +57% | 1 | 1 | 0% | 1,284 | 3,519 | +174% | 0 | 0 | — |
case-20 | fail→fail | 3,344 | 20,008 | +498% | 1 | 1 | 0% | 496 | 3,133 | +532% | 0 | 0 | — |
case-21 | pass→pass | 11,036 | 3,435 | -69% | 1 | 1 | 0% | 1,849 | 2,971 | +61% | 0 | 0 | — |
case-22 | pass→pass | 13,459 | 7,621 | -43% | 1 | 1 | 0% | 1,310 | 3,017 | +130% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 11 counted toward the lift figure. The other 11 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +18 percentage points is the difference between those two pass rates over the 11 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.