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 mh-language/mhl-core-runtime --skill mhl-servinggit clone --depth 1 https://github.com/mh-language/mhl-core-runtimeWrote 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/mh-language/mhl-core-runtime/mhl-serving)<a href="https://agentmods.dev/skills/mh-language/mhl-core-runtime/mhl-serving"><img src="https://agentmods.dev/badge/skills/mh-language/mhl-core-runtime/mhl-serving/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/mh-language/mhl-core-runtime/mhl-serving"><img src="https://agentmods.dev/badge/skills/mh-language/mhl-core-runtime/mhl-serving.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00061 | $0.01723 |
| Opus 5.5 | $0.00024 | $0.00689 |
| Sonnet 5.5 | $0.00012 | $0.00345 |
| Haiku 4.5 | $0.00006 | $0.00172 |
Grade A, and why
mhl-serving 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 today.
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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mhl serving
Assumes the mhl-language and mhl-workflows skills. mhl serve turns a directory of
.mh files into a server with no server code: each pipeline, workflow or alias becomes
one MCP tool or A2A skill, published by the file that declares it. This skill is the
server side. Calling someone else's server is extension mcp, covered in mhl-tools.
Design the workflow as an API
The declaration is the tool contract, so write it for the calling model:
enum Severity { low, high }
type TriageInput = { title: string, body: string, severity?: Severity }
type TriageOutput = { priority: string, reason: string }
tool Rules {
priority(title: string): string -> if (title.contains("outage")) "urgent" else "normal"
}
// The description is all a calling model sees, so state what the tool does.
workflow TriageIssue(req: TriageInput): TriageOutput {
description: "Classifies an incoming issue and explains the priority."
var priority = "normal"
step Classify {
self.priority = Rules.priority(req.title)
}
output: {
priority: priority
reason: "matched on title: ${req.title}"
}
}
test triage_issue {
describe outage_is_urgent {
var result = TriageIssue.run(inputs: {title: "api outage", body: "down"})
are_equal(result.output.priority, "urgent")
}
}
| Declared | Becomes |
|---|---|
description: "..." |
tool description; otherwise a generic Runs the mhl workflow "X". |
typed signature or input x: T |
inputSchema, unknown inputs rejected |
x?: field, or input x: T = default |
optional in inputSchema |
enum type |
"enum": [...] list, so callers see legal values |
: Out result type |
outputSchema; a successful result is structuredContent checked against it |
output: |
exactly the keys returned; without it, every var is returned |
Then shape the surface:
- Mark helpers
internal workflow. Publish only what callers should invoke. - Use aliases to publish one flow as several narrow tools:
workflow Delivery = ArtifactFlow with { level: Level.delivery } { description: "..." }. - Always declare
output:on a served workflow. It keeps intermediate state, prompts and tokens out of responses. - A workflow imported by several files is published once, by its declaring file.
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.
- today First seen · 156 lines · 61 tokens per session scan A f366592da142
mhl-serving is a skill published in the GitHub repository mh-language/mhl-core-runtime (9 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 1,723 once invoked, about $0.0002 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 2026-11-07.
mhl-serving compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mhl-servingmh-language/mhl-core-runtime | Skill | 9 | today | MIT | A | 61 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |