Dynamic Workflow Mode
affaan-m/ECC
Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses.
Solving finite-horizon LQR via dynamic programming for MPC. An agent skill from benchflow-ai/skillsbench.
Apache-2.0Auto-check passed
Install Finite Horizon Lqr
$ npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/skillsbench finite-horizon-lqr --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr .claude/skills/finite-horizon-lqr && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "finite-horizon-lqr" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr into .claude/skills/finite-horizon-lqr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finite-horizon-lqr", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqrType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/skillsbench finite-horizon-lqr --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr .agents/skills/finite-horizon-lqr && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "finite-horizon-lqr" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr into .agents/skills/finite-horizon-lqr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finite-horizon-lqr", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/skillsbench finite-horizon-lqr --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr .cursor/skills/finite-horizon-lqr && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "finite-horizon-lqr" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr into .cursor/skills/finite-horizon-lqr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finite-horizon-lqr", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/benchflow-ai/skillsbench.git --path tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/skillsbench finite-horizon-lqr --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr .gemini/skills/finite-horizon-lqr && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "finite-horizon-lqr" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr into .gemini/skills/finite-horizon-lqr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finite-horizon-lqr", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install benchflow-ai/skillsbench finite-horizon-lqrInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr .github/skills/finite-horizon-lqr && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "finite-horizon-lqr" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr into .github/skills/finite-horizon-lqr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finite-horizon-lqr", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install benchflow-ai/skillsbench finite-horizon-lqr --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr .opencode/skills/finite-horizon-lqr && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "finite-horizon-lqr" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr into .opencode/skills/finite-horizon-lqr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finite-horizon-lqr", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
finite-horizon-lqr- GitHub stars
- 1.8k
- Token cost
- ~270 tokens
- SKILL.md length
- 60 words
- Files
- 1
- Skills in repo
- 189
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Solving finite-horizon LQR via dynamic programming for MPC. An agent skill from benchflow-ai/skillsbench.
- Works in 4 steps: Measure current state x → Solve finite-horizon LQR from x → Apply first control u_0 → …
- SKILL.md covers Problem Formulation, Backward Riccati Recursion, Forward Simulation and Python Implementation, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Finite Horizon Lqr is an agent skill from benchflow-ai/skillsbench. Solving finite-horizon LQR via dynamic programming for MPC.
Its SKILL.md is about 270 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: SkillsBench evaluates how well skills work and how effective agents are at using them. The licence is Apache-2.0.
Example prompts
- “/finite-horizon-lqr”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Measure current state x
- Solve finite-horizon LQR from x
- Apply first control u_0
- Repeat next timestep
What it can do on your machine
Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Finite Horizon Lqr loads about 270 tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 60 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 60 words, ~270 tokens.
Download SKILL.mdSave it as
.claude/skills/finite-horizon-lqr/SKILL.md (or your agent's skills folder).- name
- finite-horizon-lqr
- description
- Solving finite-horizon LQR via dynamic programming for MPC.
Finite-Horizon LQR for MPC
Problem Formulation
Minimize cost over horizon N:
J = Σ(k=0 to N-1) [x'Qx + u'Ru] + x_N' P x_NBackward Riccati Recursion
Initialize: P_N = Q (or LQR solution for stability)
For k = N-1 down to 0:
K_k = inv(R + B'P_{k+1}B) @ B'P_{k+1}A
P_k = Q + A'P_{k+1}(A - B @ K_k)Forward Simulation
Starting from x_0:
u_k = -K_k @ x_k
x_{k+1} = A @ x_k + B @ u_kPython Implementation
def finite_horizon_lqr(A, B, Q, R, N, x0):
nx, nu = A.shape[0], B.shape[1]
K = np.zeros((nu, nx, N))
P = Q.copy()
# Backward pass
for k in range(N-1, -1, -1):
K[:,:,k] = np.linalg.solve(R + B.T @ P @ B, B.T @ P @ A)
P = Q + A.T @ P @ (A - B @ K[:,:,k])
# Return first control
return -K[:,:,0] @ x0MPC Application
At each timestep:
- Measure current state x
- Solve finite-horizon LQR from x
- Apply first control u_0
- Repeat next timestep
© benchflow-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr of benchflow-ai/skillsbench.
Open the folder on GitHubat commit 9a1f4dd
Compare with similar skills
Finite Horizon Lqr next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Finite Horizon Lqr this skillbenchflow-ai/skillsbench | 1.8k | — | ~270 | Automated safety check: Pass | Apache-2.0 | |
| Dynamic Workflow Modeaffaan-m/ECC | 277k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Horizon Trackruvnet/ruflo | 74k | — | ~744 | Automated safety check: Notes | MIT | |
| Configuring Horizoncoollabsio/coolify | 63k | 4 repos | ~898 | Automated safety check: Pass | MIT | |
| Molecular DynamicsK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Accint Solvesickn33/agentic-awesome-skills | 47k | 1 repos | ~520 | Automated safety check: Pass | Apache-2.0 |
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ruvnet/ruflo
Track long-horizon objectives across multiple sessions with milestone checkpoints, progress persistence, and drift detection
Configuring Horizon
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Molecular Dynamics
K-Dense-AI/scientific-agent-skills
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Questions about Finite Horizon Lqr
What does Finite Horizon Lqr do?
Solving finite-horizon LQR via dynamic programming for MPC. An agent skill from benchflow-ai/skillsbench. Finite Horizon Lqr is an agent skill from benchflow-ai/skillsbench. Solving finite-horizon LQR via dynamic programming for MPC.
How do I install Finite Horizon Lqr in Claude Code?
Run `npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a claude-code`. Or copy the skill folder (tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr in benchflow-ai/skillsbench) into .claude/skills/finite-horizon-lqr in your project. Claude Code loads it when a task matches its description.
How do I install Finite Horizon Lqr in Codex?
Run `npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a codex`. Or copy the skill folder (tasks/r2r-mpc-control/environment/skills/finite-horizon-lqr in benchflow-ai/skillsbench) into .agents/skills/finite-horizon-lqr in your project. Codex loads it when a task matches its description.
Can I use Finite Horizon Lqr in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add benchflow-ai/skillsbench --skill finite-horizon-lqr -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/finite-horizon-lqr, .gemini/skills/finite-horizon-lqr, .github/skills/finite-horizon-lqr and .opencode/skills/finite-horizon-lqr in your project.
What does Finite Horizon Lqr need to run?
SKILL.md names no scripts, command-line tools or credentials: Finite Horizon Lqr is instructions for the agent only. Our summary lists: Python 3.
Does Finite Horizon Lqr access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Finite Horizon Lqr safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Finite Horizon Lqr use?
Finite Horizon Lqr is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Finite Horizon Lqr use?
About 270 tokens (SKILL.md is roughly 1.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Finite Horizon Lqr?
Skills that share tags, products or a category with Finite Horizon Lqr: Dynamic Workflow Mode (affaan-m/ECC, 277k stars), Horizon Track (ruvnet/ruflo, 74k stars), Configuring Horizon (coollabsio/coolify, 63k stars) and Molecular Dynamics (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Finite Horizon Lqr?
benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,835 GitHub stars. The repository holds 189 skills in this directory. The repository was last updated on July 23, 2026.
Source: benchflow-ai/skillsbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.