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/lukas-grigis/ralphctl/harness-engineeringnpx skills add lukas-grigis/ralphctl --skill harness-engineeringgit clone --depth 1 https://github.com/lukas-grigis/ralphctlWrote 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/lukas-grigis/ralphctl/harness-engineering)<a href="https://agentmods.dev/skills/lukas-grigis/ralphctl/harness-engineering"><img src="https://agentmods.dev/badge/skills/lukas-grigis/ralphctl/harness-engineering.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 | $0.00096 | $0.03581 |
| Opus 5 | $0.00048 | $0.01791 |
| Sonnet 5 | $0.00019 | $0.00716 |
| Haiku 4.5 | $0.00010 | $0.00358 |
Grade A, and why
harness-engineering 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Harness Engineering — article-grounded reference
A themed synthesis of three Anthropic engineering articles on building harnesses for agentic and long-running coding work. This is the reference / the why. Two siblings carry the other halves:
harness-principles(skill) — the lightweight read-first trigger for structural changes..claude/docs/HARNESS-PRINCIPLES.md— the ralphctl status map (each principle taggedapplied/partial/gapwith a code anchor).
This skill does not restate those. It distills the source articles by theme, keeps the load-bearing verbatim quotes with attribution, and ends with a brief pointer to where each idea lives in ralphctl. Citation labels below map to the Sources section. Open the original when a rationale needs full framing.
1. Climb the complexity ladder reluctantly (workflow vs agent)
The vocabulary first. Workflows are "systems where LLMs and tools are orchestrated through predefined code paths"; agents are "systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks" (Building Effective Agents). Most production work wants the predictability of a workflow, not the open-endedness of an agent.
The ladder ascends from a direct API call → the augmented LLM (retrieval / tools / memory) → a single workflow pattern → composed workflows → an autonomous agent. Five workflow patterns are named: prompt chaining, routing, parallelization (sectioning + voting), orchestrator-workers, and evaluator-optimizer. You climb a rung only when the lower one demonstrably fails.
"Consistently, the most successful implementations weren't using complex frameworks or specialized libraries. Instead, they were building with simple, composable patterns." — Building Effective Agents
"You should consider adding complexity only when it demonstrably improves outcomes." — Building Effective Agents
Corollary: invest in the agent-computer interface (ACI) as much as a human UI — tool docs, examples, and poka-yoke (e.g. absolute over relative filepaths) earn their keep. Frameworks "often create extra layers of abstraction that can obscure the underlying prompts and responses, making them harder to debug."
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 · 215 lines · 96 tokens per session scan A 330e695ff6fe
harness-engineering is a skill published in the GitHub repository lukas-grigis/ralphctl (23 stars, last pushed today), licensed MIT. It adds 96 tokens to every session and 3,581 once invoked, about $0.0005 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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