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 jpantsjoha/ai-native-developer-experience --skill delivery-orchestratorgit clone --depth 1 https://github.com/jpantsjoha/ai-native-developer-experienceWrote 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/jpantsjoha/ai-native-developer-experience/delivery-orchestrator)<a href="https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/delivery-orchestrator"><img src="https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/delivery-orchestrator.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00065 | $0.00960 |
| Opus 5 | $0.00032 | $0.00480 |
| Sonnet 5 | $0.00013 | $0.00192 |
| Haiku 4.5 | $0.00006 | $0.00096 |
Grade A, and why
delivery-orchestrator 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 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.
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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delivery Orchestrator
A skill for choosing skills. Once your harness grows past a handful of skills, the agent needs a way to select the right one. This is that skill.
The orchestrator has two jobs: decompose work into the smallest independently executable units, then route each unit to the skill that owns it.
When to use
- Starting a new epic or multi-track piece of work
- When an agent is about to attempt everything in one context window
- When parallel execution across multiple agents is needed
- When you need to decide which skill applies to an incoming task
Procedure
Part 1 — Decomposition
- Read the spec or brief — confirm a feature spec or HLD exists. If not, invoke
spec-first-deliveryfirst. - Identify tracks — group work into independent tracks (e.g. backend API, frontend, infrastructure, testing). Tracks can run in parallel. Dependencies between tracks must be explicit.
- Break each track into atomic tasks — an atomic task is one that:
- Can be assigned to a single agent
- Has a clear input and a clear output
- Does not require coordination with another concurrent task to complete
- Can be validated independently
- Sequence dependencies — where task B requires output from task A, mark the dependency. Everything else is parallel.
- Assign context boundaries — each agent gets only the context it needs. Avoid stuffing all specs into every agent's context.
Part 2 — Skill routing
- Map each task to a skill using the routing table below. If no skill matches exactly, use the closest and note the gap.
- Validate integration after parallel work — run the full regression suite (
make checkor the project's equivalent convergence command) after all parallel tracks complete. Parallel work that skips integration validation is not done.
Skill routing table
| Task type | Route to skill |
|---|---|
| New feature / epic planning | spec-first-delivery |
| Architecture decision or trade-off | the-architect |
| High-stakes design review | adversarial-gate |
| Pre-deployment go/no-go | release-readiness |
| Release process governance, SemVer, ADR, changelog | release-manager |
| Enterprise policy, compliance, or governance alignment | governance-guardrail |
| GitHub repo operations: CI triggers, billing, issues, labels, branch protection | github-manager |
| Google ADK agent patterns | adk-expert |
| Cloud infrastructure guardrails | gcp-expert / aws-expert / azure-expert / alibaba-expert |
| MCP server design or governance | mcp-server-scaffold |
| Agent output validation | domain-validator |
| PR or code review | pr-reviewer |
| LLM cost or model selection | cost-guardrail |
| Status or standup synthesis | sitrep |
| Plugin-directory, marketplace, or curated-list submission | plugin-submission |
| New repo or operating model install / repair | operating-model-bootstrap |
| Delivery controls: source of truth, issue/PR conventions, DoD, escalation | delivery-orchestrator (own it here) |
| Routing this list | delivery-orchestrator (you are here) |
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 · 74 lines · 65 tokens per session scan A 4160de09da89
delivery-orchestrator is a skill published in the GitHub repository jpantsjoha/ai-native-developer-experience (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 65 tokens to every session and 960 once invoked, about $0.0003 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 2026-08-30.
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