mpc-horizon-tuning SKILL.md skillA
mpc-horizon-tuning from benchflow-ai/benchflow is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add benchflow-ai/benchflow/mpc-horizon-tuning@git:20260610.e2a435fPins git:20260610.e2a435f in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- benchflow-ai/benchflow
- Path
tests/fixtures/skillsbench_slice/r2r-mpc-control/environment/skills/mpc-horizon-tuning/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260610.e2a435f, committed Jun 10, 2026
- Size
- 1,197 bytes
- Repository stars
- 359
- License
- Apache-2.0
Selecting MPC prediction horizon and cost matrices for web handling.
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
# MPC Tuning for Tension Control ## Prediction Horizon Selection **Horizon N** affects performance and computation: - Too short (N < 5): Poor disturbance rejection - Too long (N > 20): Excessive computation - Rule of thumb: N ≈ 2-3× settling time / dt For R2R systems with dt=0.01s: **N = 5-15** typical ## Cost Matrix Design **State cost Q**: Emphasize tension tracking ```python Q_tension = 100 / T_ref² # High weight on tensions Q_velocity = 0.1 / v_ref² # Lower weight on velocities Q = diag([Q_tension × 6, Q_velocity × 6]) ``` **Control cost R**: Penalize actuator effort ```python R = 0.01-0.1 × eye(n_u) # Smaller = more aggressive ``` ## Trade-offs | Higher Q | Effect | |----------|--------| | Faster tracking | More control effort | | Lower steady-state error | More aggressive transients | | Higher R | Effect | |----------|--------| | Smoother control | Slower response | | Less actuator wear | Higher tracking error | ## Terminal Cost Use LQR solution for terminal cost to guarantee stability: ```python P = solve_continuous_are(A, B, Q, R) ```
Read the whole file at its exact version.
How to install
mdr add benchflow-ai/benchflow/mpc-horizon-tuning@sha256:fa85a6c22e728d92The line at the top of this page pins the label git:20260610.e2a435f, 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_m3655x5btgew2vyu)
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Versions
The registry has recorded 1 version of this file, committed on Jun 10, 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 (1197 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
benchflow-ai/benchflow · 359 stars · license Apache-2.0 · pushed 2026-10-30 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_m3655x5btgew2vyu GET https://markdownregistry.com/api/v1/resolve?ref=benchflow-ai/benchflow/mpc-horizon-tuning GET https://markdownregistry.com/api/v1/blob/fa85a6c22e728d92176f4aace0a3ad65e280bd4ecd061d1037a042b29ec47123
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.