Agent skill for matrix-optimizer - invoke with $agent-matrix-optimizer
42
Quality
13%
Does it follow best practices?
Impact
87%
1.40xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-matrix-optimizer/SKILL.mdMatrix property analysis workflow
Diagonal dominance check
100%
100%
Symmetry check
100%
100%
Condition number estimation
100%
100%
Spectral gap computation
30%
70%
Dominance failure recommendation
41%
100%
Analysis-before-solve ordering
100%
100%
Structured JSON report
80%
100%
Preprocessing phase present
10%
60%
Validation phase present
0%
12%
Error handling
40%
0%
Without context: $0.3832 · 1m 37s · 20 turns · 25 in / 6,168 out tokens
With context: $0.8339 · 3m 16s · 33 turns · 39 in / 12,716 out tokens
Sparse solver method and convergence parameters
COO format structure
50%
100%
Neumann series method
0%
100%
Epsilon 1e-8
0%
100%
MaxIterations 1000
0%
100%
Pre-solve dominance check
100%
100%
Preprocessing for non-dominant
20%
30%
Solution report output
100%
100%
Error handling
62%
62%
Analysis before solve ordering
100%
100%
Validation phase
50%
50%
Without context: $0.4393 · 1m 50s · 25 turns · 31 in / 6,157 out tokens
With context: $0.6508 · 2m 45s · 27 turns · 436 in / 9,548 out tokens
Targeted entry estimation parameters
Random-walk method
66%
100%
Epsilon 1e-6
16%
100%
Confidence 0.95
100%
100%
Pre-estimation matrix analysis
100%
100%
Diagonal dominance check
100%
100%
Condition number estimation
100%
100%
Entry-specific targeting
100%
100%
Estimation report output
100%
100%
Error handling
50%
100%
Analysis-before-estimation ordering
100%
100%
Without context: $0.4364 · 2m 19s · 17 turns · 20 in / 8,709 out tokens
With context: $0.7714 · 3m 38s · 32 turns · 288 in / 10,722 out tokens
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Table of Contents
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