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Constrained Optimization · vibeeval | DecimalAI

scienceby vibeeval

Constrained Optimization

vibeeval/constrained-optimization

Source vibeeval/vibecosystem ↗License MIT

Problem-solving strategies for constrained optimization in optimization

SkillScore100Maintained

Automatic

Research pack

Last verified 8/3/2026

What it changes

Passed 22 of 22 test cases with the skill, and 20 of 22 without it.

Without skill91%

With skill100%

Checks it passed that the model alone missed

Calls sympy_compute.py with the solve command
Invokes z3_solve.py with the prove command target

2 fixed20 passed either way0 still failing0 broke

Pass-rate lift: +9 pp
Tokens: +28%
Agent turns: 0%
Response time: -34%

Model gemini-3.6-flashMeasured 8/3/2026v122 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/vibeeval-constrained-optimization/SKILL.md https://app.decimal.ai/s/vibeeval-constrained-optimization/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add vibeeval-constrained-optimization, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/vibeeval-constrained-optimization/ and pins it in .decimal/skills.lock

decimalai skills add vibeeval-constrained-optimization

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/vibeeval-constrained-optimization/SKILL.md https://app.decimal.ai/s/vibeeval-constrained-optimization/SKILL.md

Raw file: /s/vibeeval-constrained-optimization/SKILL.md ↗ · machine-readable summary at /s/vibeeval-constrained-optimization.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 2

Prompt

I need to symbolically find the critical points for a system derived from setting the gradient of the Lagrangian to zero. Which symbolic computation script target handles solving algebraic derivative systems?

What was checked, without and with the skill
Checked	Without skill	With skill
Calls sympy_compute.py with the solve command	Missed	Passed

case-08 · gemini-3.6-flash · 8/3/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md65 linessingle file

Constrained Optimization

When to Use

Use this skill when working on constrained-optimization problems in optimization.

Decision Tree

Constraint Classification
- Equality: h(x) = 0
- Inequality: g(x) <= 0
- Bounds: l <= x <= u
Lagrangian Method (Equality Constraints)
- L(x, lambda) = f(x) + sum lambda_j * h_j(x)
- Solve: grad_x L = 0 and h(x) = 0
- sympy_compute.py solve "grad_L_system"
KKT Conditions (Inequality Constraints)
- Extend Lagrangian with mu_i for g_i(x) <= 0
- Complementary slackness: mu_i * g_i(x) = 0
- z3_solve.py prove "kkt_satisfied"
Penalty and Barrier Methods
- Penalty: add P(x) = rho * sum max(0, g_i(x))^2
- Barrier: add B(x) = -sum log(-g_i(x)) for interior point
- Increase penalty/decrease barrier parameter iteratively
SciPy Constrained Optimization
- scipy.optimize.minimize(f, x0, method='SLSQP', constraints=cons)
- constraints = [{'type': 'eq', 'fun': h}, {'type': 'ineq', 'fun': lambda x: -g(x)}]
- bounds = [(l1, u1), (l2, u2), ...]

Tool Commands

Scipy_Slsqp

uv run python -c "from scipy.optimize import minimize; cons = dict(type='eq', fun=lambda x: x[0] + x[1] - 1); res = minimize(lambda x: x[0]**2 + x[1]**2, [1, 1], method='SLSQP', constraints=cons); print('Min at', res.x)"

Track record

Benchmark

22 / 22

test cases passed, vs 20 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/1/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

vibeeval / vibecosystem

skills/math/optimization/constrained-optimization/SKILL.md

View on GitHub ↗

License MITImported 8/1/2026Version v1

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

vibeeval/convex-optimizationProblem-solving strategies for convex optimization in optimizationClose match+14 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Constrained Optimization

When to Use

Decision Tree

Tool Commands

Scipy_Slsqp

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

Related skills