agent-matrix-optimizer

Agent skill for matrix-optimizer - invoke with $agent-matrix-optimizer

1.40x

Quality

Does it follow best practices?

Impact

87%

1.40x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-matrix-optimizer/SKILL.md

Evaluation results

76%

15%

Matrix Solver Readiness Analysis Tool

Matrix property analysis workflow

Criteria

Without context

With context

Diagonal dominance check

100%

Symmetry check

100%

Condition number estimation

100%

Spectral gap computation

30%

70%

Dominance failure recommendation

41%

100%

Analysis-before-solve ordering

100%

Structured JSON report

80%

100%

Preprocessing phase present

10%

60%

Validation phase present

12%

Error handling

40%

86%

41%

Large-Scale Sparse Linear System Solver

Sparse solver method and convergence parameters

Criteria

Without context

With context

COO format structure

50%

100%

Neumann series method

100%

Epsilon 1e-8

100%

MaxIterations 1000

100%

Pre-solve dominance check

100%

Preprocessing for non-dominant

20%

30%

Solution report output

100%

Error handling

62%

Analysis before solve ordering

100%

Validation phase

50%

100%

19%

Sublinear Solution Entry Estimator

Targeted entry estimation parameters

Criteria

Without context

With context

Random-walk method

66%

100%

Epsilon 1e-6

16%

100%

Confidence 0.95

100%

Pre-estimation matrix analysis

100%

Diagonal dominance check

100%

Condition number estimation

100%

Entry-specific targeting

100%

Estimation report output

100%

Error handling

50%

100%

Analysis-before-estimation ordering

100%

Repository: ruvnet/claude-flow
Commit: 01070ed

Evaluated: about 1 month ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Matrix Solver Readiness Analysis Tool Large-Scale Sparse Linear System Solver Sublinear Solution Entry Estimator

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.