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/mifunedev/openharness/render-htmlnpx skills add mifunedev/openharness --skill render-htmlgit clone --depth 1 https://github.com/mifunedev/openharnessWhat 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 | $0.00112 | $0.01731 |
| Opus 5 | $0.00056 | $0.00865 |
| Sonnet 5 | $0.00022 | $0.00346 |
| Haiku 4.5 | $0.00011 | $0.00173 |
Grade A, and why
render-html 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 2d 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Render HTML
Take an artifact (file path or in-context material) plus a one-line intent and produce a single, self-contained HTML file optimized for the moment a human reads it once to make a decision.
Core principle (from Thariq's HTML-over-Markdown thesis): every invocation produces bespoke HTML, picked widget-by-widget for this artifact. No templates. A template forces the format back into the Markdown mindset of pre-baked structure and defeats the point.
When to use
Use when all three are true:
- The artifact is a synthesis the human will read once to decide something.
- The Markdown version would exceed ~100 lines or carry signal a table/SVG/collapsible would express more cleanly (severity, dependency, status, time).
- No downstream pipeline (Ralph, GitHub, another LLM, grep) consumes the artifact.
Common targets in this harness:
/audit harnesstier-ranked report → filterable findings dashboard/strategic-proposalcouncil artifact → phase-column roadmap with critic challenges inline/audit skillsverdict matrix → sortable scoring table with CURRENT/STALE/BROKEN/DELETE badges- Weekly digest of cron liveness (
crons/.cron.log) → timeline coloured by outcome
When NOT to use
Skip when the artifact is source or pipeline input — Markdown stays the substrate of the harness:
- PRDs (
.oh/tasks/*/prd.md), briefings, commit messages, PR bodies,CHANGELOG.md - The cron liveness trail itself (
crons/.cron.log) - Skill/identity sources (
CLAUDE.md,.claude/skills/) - Agent-to-agent handoffs (advisor → executor briefings)
If asked to render any of the above, refuse and explain.
Instructions
1. Parse arguments
Arguments received: $ARGUMENTS
| Position | Meaning |
|---|---|
$0 |
slug (required, kebab-case, no extension) — becomes the filename |
--from <path> |
optional source artifact to read |
--intent <one-line> |
optional human-purpose hint (e.g. "pick next 3 audit actions") |
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.
- 2d ago First seen · 129 lines · 112 tokens per session scan A 746958dbe0c8
render-html is a skill published in the GitHub repository mifunedev/openharness (36 stars, last pushed 2d ago), licensed Apache-2.0. It adds 112 tokens to every session and 1,731 once invoked, about $0.0006 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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