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/zli12321/lhtb/create-adapternpx skills add zli12321/LHTB --skill create-adaptergit clone --depth 1 https://github.com/zli12321/LHTBWrote 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/zli12321/lhtb/create-adapter)<a href="https://agentmods.dev/skills/zli12321/lhtb/create-adapter"><img src="https://agentmods.dev/badge/skills/zli12321/lhtb/create-adapter.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 | $0.00034 | $0.01667 |
| Opus 5 | $0.00017 | $0.00834 |
| Sonnet 5 | $0.00007 | $0.00333 |
| Haiku 4.5 | $0.00003 | $0.00167 |
Grade A, and why
create-adapter 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.
This is a copy
92% identical to create-adapter — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Adapter
Bootstrap a new benchmark adapter in the Harbor repository. This skill scaffolds the adapter directory with harbor adapter init and then defers to the adapter tutorial for every implementation decision.
Authoritative reference
The adapter tutorial is the authoritative specification for this skill. Read it in full before taking any action beyond scaffolding:
docs/content/docs/datasets/adapters.mdx
That path is relative to the Harbor repo root (a skill prerequisite — see below). The tutorial contains:
- Required directory structures for the generated tasks and the adapter code package.
- Step-by-step process (steps 1-9) covering benchmark analysis, oracle verification, parity experiments, dataset registration, and submission.
- Schemas for
task.toml,parity_experiment.json,adapter_metadata.json, anddataset.toml. - Parity matching criterion, pre-flight checklist, and debug playbook.
- README format rules (machine-parsed; deviations break automation).
Do not substitute prior knowledge for the contents of that file. Treat it as the contract.
Prerequisites
- Harbor CLI is installed and available on
PATH(harbor --versionsucceeds). - Working directory is the Harbor repository root.
- Harbor checkout is current: run
git fetch origin && git statusand pullmainif behind. Stale checkouts miss recent adapter and agent fixes and are a common source of spurious parity failures later on.
Workflow
1. Read the tutorial
Before any filesystem or CLI action, Read docs/content/docs/datasets/adapters.mdx in full. Pay particular attention to:
- Required Directory Structures — the contract for generated task and adapter layouts.
- Step 1. Understand the Original Benchmark — what to identify upstream before coding.
- Step 8. Register the Dataset → Naming rules — the
namefield and<org>/<task>format requirements.
2. Gather benchmark context from the user
Collect the following before scaffolding. If the user has not provided an item, ask before proceeding — these inputs shape the scaffold and the tutorial steps that follow.
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 · 116 lines · 34 tokens per session scan A 625f08a078be
create-adapter is a skill published in the GitHub repository zli12321/LHTB (697 stars, last pushed 7d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,667 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to create-adapter, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
rewardkit
Write Harbor task verifiers using Reward Kit. Use when creating or editing a task's tests/ directory, adding grading criteria, setting up LLM/agent judges, or designing verifiers that produce a reward score.
create-adapter
Scaffold a new Harbor benchmark adapter by running harbor adapter init and then guide implementation using the Adapters Agent Guide as the authoritative spec.
upload-parity-experiments
Create or reuse Hugging Face dataset PRs for harborframework/parity-experiments and upload Harbor parity/oracle result folders efficiently with sparse checkout, raw git pushes, and Git LFS.
harbor-exec
Use when working with Harbor's harbor exec CLI workflow: compiling files, directories, or globs into Harbor tasks; running map jobs; configuring artifacts and existence-only verification; using map-reduce; writing or reviewing ExecConfig YAML/JSON/TOML; or debugging command behavior, config validation, and job outputs.
publish
Publish a Harbor task or dataset to the registry. Use when the user wants to upload, publish, or share tasks or datasets/benchmarks on the Harbor registry.
generate-greeting
Generate a greeting message and write it to a file.