constrained-optimization SKILL.md skillA
constrained-optimization from magnus919/agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add magnus919/agent-skills/constrained-optimization@git:20260914.f53bddcPins git:20260914.f53bddc in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- magnus919/agent-skills
- Path
constrained-optimization/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260914.f53bddc, committed Sep 14, 2026
- Size
- 3,883 bytes
- Repository stars
- 166
- License
- MIT
Define, compare, and audit constrained optimization decisions with explicit variables, units, hard and soft constraints, feasibility, Pareto tradeoffs, and honest solver evidence. Do not use for statistical modeling or ML fitting, which belong to data-scientist or ml-engineering, or for operating a named solver.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Constrained optimization Use this methodology to turn an optimization request into a defensible decision record. ## Workflow 1. **Frame the decision.** Name the decision maker, feasible action window, variable domains (continuous, integer, categorical, binary), bounds, units, and whether each variable is controllable. 2. **State objectives.** Write objective direction, units, aggregation, baseline, and acceptable tradeoffs. Keep multiple objectives separate until a decision maker chooses weights, lexicographic priority, epsilon constraints, or a Pareto review. 3. **Classify constraints.** Mark each as hard (must hold), soft (preference with an explicit penalty or relaxation), or informational. Define equality/inequality tolerance, feasibility predicate, and how violations are measured. Never hide a hard violation in a penalty score. 4. **Establish baselines.** Validate a known feasible incumbent, a simple exact or bounded baseline where available, and a heuristic baseline when exact solving is impractical. State what each baseline proves and does not prove. …
Read the whole file at its exact version.
How to install
mdr add magnus919/agent-skills/constrained-optimization@sha256:29871425d561ca83The line at the top of this page pins the label git:20260914.f53bddc, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_gnljilhhmmrmnjf7)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Sep 14, 2026.
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 (3883 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
magnus919/agent-skills · 166 stars · license MIT · pushed 2026-11-04 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_gnljilhhmmrmnjf7 GET https://markdownregistry.com/api/v1/resolve?ref=magnus919/agent-skills/constrained-optimization GET https://markdownregistry.com/api/v1/blob/29871425d561ca830b00caee84330afb2aa973b991295afbf0b3eb32b5f080a5
Your AI assistant 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.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.