harness-engineering skillA
harness-engineering is agent-read markdown (skill) from habitat-thinking/ai-literacy-superpowers: This skill should be used when the user asks about "harness engineering", "what is a harness", "harness framework", "AI code quality", "context engineering", "architectural constraints", "garbage collection for code", or wants to understand the conceptual foundation behind the harness-engineering plugin..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Harness Engineering A harness is the combined set of deterministic tooling and LLM-based agents that keeps AI code generation trustworthy and maintainable at scale. The concept originates from Birgitta Boeckeler's article "Harness Engineering" (2026), which identifies three components that together form a complete harness. For the full article summary and four hypotheses, consult `references/boeckeler-summary.md`. ## The Three Components ### Context Engineering The knowledge an LLM needs to work effectively in a codebase. This includes explicit documentation (conventions, constraints, stack declarations) and implicit context (the code design itself). A well-structured codebase is easier to harness than a sprawling one because the structure communicates intent. In this plugin, context engineering lives in HARNESS.md's **Context** section — stack declaration, convention documentation, and any project-specific knowledge that shapes how code should be written. ### Architectural Constraints Rules that must be enforced — not suggestions, but hard boundaries. Each constraint is backed by a **verification slot** that can be filled …
Read the whole file at its exact version.
How to install
mdr add habitat-thinking/ai-literacy-superpowers/harness-engineering@git:20260414.89199femdr add habitat-thinking/ai-literacy-superpowers/harness-engineering@sha256:12b5785979500e7fPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_b66huxv6ywujga4y)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260414.89199fe latest | 2026-04-14 | 89199fe | 5,791 B | A | view · diff |
| git:20260406.60a61ca | 2026-04-06 | 60a61ca | 4,249 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5791 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
habitat-thinking/ai-literacy-superpowers · 106 stars · license NOASSERTION · pushed 2026-09-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_b66huxv6ywujga4y GET https://markdownregistry.com/api/v1/resolve?ref=habitat-thinking/ai-literacy-superpowers/harness-engineering GET https://markdownregistry.com/api/v1/blob/12b5785979500e7f564614de10e234392c76807e0f2ee463e3b6c442d0a56a33
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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