apiliumcode/model-advisor
skills/official/model-advisor/SKILL.md
Recommends the optimal Claude model based on task requirements and cost analysis
$ install --global
skillsauthnpx skillsauth add apiliumcode/mayros model-advisorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
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CrowdStrikeAdvanced threat intelligence
50%
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OSV-ScannerOpen Source Vulnerability database check
50%
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OWASP Dep-Check
50%
Last scanned: Apr 4, 2026, 4:16 AM5.5s8 files scanned
SKILL.md
- name:
- model-advisor
- description:
- Recommends the optimal Claude model based on task requirements and cost analysis
- type:
- semantic
- user-invocable:
- true
- skillVersion:
- 1
- graph:
- [read]
- memory:
- [recall]
- - predicate:
- advisor:recommendation
- scope:
- agent
model-advisor
Recommends the optimal Claude model based on task requirements, complexity analysis, and cost efficiency.
When to Use
Use when choosing between Claude models for a specific task, when optimizing API costs, or when you need guidance on which model best fits a workload profile.
Supported Models
| Model | Input | Output | Best For | | ---------- | ---------- | -------- | ------------------------------------------------------------------------------------- | | Opus 4.6 | $15/MTok | $75/MTok | Complex reasoning, research, multi-step analysis, code architecture, creative writing | | Sonnet 4.6 | $3/MTok | $15/MTok | Coding, general tasks, data analysis, moderate complexity | | Haiku 4.5 | $0.80/MTok | $4/MTok | Classification, extraction, simple Q&A, high volume, low latency |
Instructions
- Recall any previous model recommendations with
skill_memory_context - Analyze the task description from query results for complexity indicators
- Match task keywords against model strengths to determine the best fit
- Return the recommended model with rationale and cost comparison
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