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 agentmods add skills/jpantsjoha/ai-native-developer-experience/using-the-harnessnpx skills add jpantsjoha/ai-native-developer-experience --skill using-the-harnessgit 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/using-the-harness)<a href="https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/using-the-harness"><img src="https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/using-the-harness.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 | $0.00063 | $0.01338 |
| Opus 5 | $0.00032 | $0.00669 |
| Sonnet 5 | $0.00013 | $0.00268 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
using-the-harness 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 5d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using the Harness
This is a team operating harness: one shared contract for humans and AI agents working in the same repository — same rules, same risk tiers, same evidence, same definition of done. It exists to make a mixed human–AI team coherent, not to make one agent faster.
A skill supplies a repeatable procedure. It never supplies permission or accountability.
First actions, every session
- Ground in the contract. If this project has adopted the operating model, read its
project profile before anything else (
docs/operating-model/PROJECT-OPERATING-PROFILE.md), then the manual it binds. Profile facts beat inference. - Classify risk before acting. Map the requested work to R0–R3. Round ambiguity upward. Confirm authority at that tier before any consequential, destructive, external, or credential-touching action.
- Route before doing. Check the routing table below. If a skill applies to the
work, use it. If you are unsure which applies, use
delivery-orchestrator.
Core invariants — not negotiable
- Classify risk before confirming authority. Approval is scoped to actual risk.
- Infer intent; never infer permission. Useful intent is not a grant of authority.
- Receipts, not polish. Produce an artefact or a pass/fail verdict, not a narrative.
- Review binds to the exact candidate. Any change after review invalidates it.
seedis notactive. A seed profile supports design and R0/R1 work only.- Never invent a project fact. Unknowns get an owner and a resolving trigger.
- Insufficient evidence is a stop, not a prompt to improvise. Tag the roster role that owns the decision; silence never converts to permission.
Skill routing
| Work in front of you | Skill |
|---|---|
| New repo, or operating model install/repair | operating-model-bootstrap |
| Multi-track epic, or "which skill applies?" | delivery-orchestrator |
| Significant technical decision or ADR | the-architect |
| New feature, epic, or change — plan before code | spec-first-delivery |
| High-stakes decision, or before claiming done | adversarial-gate |
| Agent output feeding a decision, store, or another agent | domain-validator |
| Any PR or agent-generated code before commit | pr-reviewer |
| Anything about to ship to a real environment | release-readiness |
| CI triggers, Actions billing, issues, labels, branch protection, or release-tag workflow | github-manager |
| Release process governance: SemVer, ADR, changelog, release authority | release-manager |
| Enterprise policy, compliance, governance, or approved-vendor alignment | governance-guardrail |
| Status, standup, or situation report | sitrep |
| Plugin-directory, marketplace, or curated-list submission | plugin-submission |
| LLM/cloud cost estimate or architecture with LLM calls | cost-guardrail |
| Google ADK multi-agent design | adk-expert |
| Any cloud-vendor workload | gcp-expert / aws-expert / azure-expert / alibaba-expert (the-architect routes) |
| Adding or reviewing an MCP server | mcp-server-scaffold |
What ships with it
1 file 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.
- 5d ago First seen · 100 lines · 63 tokens per session scan A 307945b1ab90
using-the-harness is a skill published in the GitHub repository jpantsjoha/ai-native-developer-experience (11 stars, last pushed 29d ago), licensed Apache-2.0. It adds 63 tokens to every session and 1,338 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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