agent-usage-optimizer-keyword-route-classification
Sub-skill of agent-usage-optimizer: Keyword → Route classification.
Best use case
agent-usage-optimizer-keyword-route-classification is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of agent-usage-optimizer: Keyword → Route classification.
Teams using agent-usage-optimizer-keyword-route-classification should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/keyword-route-classification/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-usage-optimizer-keyword-route-classification Compares
| Feature / Agent | agent-usage-optimizer-keyword-route-classification | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of agent-usage-optimizer: Keyword → Route classification.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Keyword → Route classification
## Keyword → Route classification
```
Compound / Route C keywords:
architecture, design, system, multi-file, refactor, security review,
cross-repo, orchestrat, compound, plan, spec
Standard / Route B keywords:
implement, feature, review, documentation, test, bug, fix, config,
update, migrate, integration
Simple / Route A keywords:
generate, scaffold, unit test, snippet, function, debug, format,
check, validate, search, grep
Bulk keywords:
summarise, summarize, batch, bulk, all files, across repos, report
Long-context keywords:
large file, full repo, 1000 lines, entire codebase, cross-repo scan
```
Output format for ad-hoc recommendation:
```
Task: "implement OAuth login for the API"
Route: B (Standard)
Primary: Codex Sonnet [quota: <Codex>% — OK]
Secondary: Codex [quota: <CODEX>% — OK]
Rationale: Standard feature implementation with moderate complexity.
Sonnet provides quality output within quota headroom.
Codex is secondary for focused function-level generation.
```Related Skills
boundary-policy-classification-by-role
Classify artifacts as durable vs transient by their functional role rather than directory path, using multi-layer architectural validation
provider-audit-bootstrap-and-path-classification
Fix provider-session ecosystem audit failures caused by source-checkout imports and over-aggressive symbolic-path classification.
pdf-text-extractor-readability-classification
Sub-skill of pdf-text-extractor: Readability Classification.
seo-optimizer
SEO optimization toolkit with scoring, keyword research, and technical SEO auditing. Use for improving search rankings, content optimization, and technical SEO fixes. Based on alirezarezvani/Codex-skills.
usage-optimization
Optimize AI usage efficiency through script-first patterns, batch operations, and input preparation
agent-usage-optimizer
Reads quota state and recommends optimal Codex/Codex/Gemini allocation per task
skill-creator-advanced-usage
Sub-skill of skill-creator: Advanced Usage.
usage-tracker-5-trend-analysis
Sub-skill of usage-tracker: 5. Trend Analysis (+1).
usage-tracker-3-usage-summary-reports
Sub-skill of usage-tracker: 3. Usage Summary Reports (+1).
usage-tracker-1-basic-usage-logging
Sub-skill of usage-tracker: 1. Basic Usage Logging (+1).
complexity-scorer-1-keyword-based-scoring
Sub-skill of complexity-scorer: 1. Keyword-Based Scoring (+1).
gmsh-openfoam-orcaflex-agent-usage-pattern
Sub-skill of gmsh-openfoam-orcaflex: Agent Usage Pattern.