Agent skill

Use the Best Tool

Detect available CLI tools, select optimal tool for tasks, research alternatives when tools underperform. Use when choosing between CLI tools, tool seems slow or limited, need to search/view/process files, checking available tooling.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/use-the-best-tool

SKILL.md

Use the Best Tool

Select optimal CLI tools → graceful fallback → research when needed.

<when_to_use>

  • Choosing which tool for file search, content search, JSON processing
  • Tool taking unexpectedly long for task size
  • User expresses frustration with current tool
  • Task could be done more elegantly
  • Need to verify tool availability before recommending

NOT for: tasks where tool choice is predetermined, simple one-line commands

</when_to_use>

Run detection script before selecting tools:

bash
bun /Users/mg/Developer/outfitter/agents/baselayer/skills/use-the-best-tool/scripts/index.ts

Parse output to determine:

  • Available modern tools
  • Missing tools that could enhance workflow
  • System context (OS, package managers)

Cache results per session — no need to re-run unless tool availability changes.

Map task to best available tool:

Task Preferred Fallback Legacy Notes
Find files by name fd - find fd: faster, better defaults
Search file contents rg - grep rg: respects .gitignore, faster
AST-aware code search sg rg grep sg: structure-aware queries
Process JSON jq - python/node jq: domain-specific language
View file with syntax bat - cat bat: syntax highlighting, git diff
List directory eza - ls eza: modern output, icons
View git diff delta - git diff delta: side-by-side, syntax highlighting
Navigate directories zoxide - cd zoxide: frecency-based jumping
Fuzzy select fzf - - fzf: interactive filtering
HTTP requests httpie - curl httpie: human-friendly syntax

Selection algorithm:

  1. Check detection results for preferred tool
  2. If available → use with optimal flags
  3. If unavailable → check fallback column
  4. If no fallback → use legacy with best-effort flags
  5. Note gap if preferred tool would significantly improve workflow

When preferred tool unavailable:

Minor improvement (preferred 10–30% better):

  • Use next best option silently
  • Don't interrupt workflow

Significant improvement (preferred 2x+ better):

  • Use fallback
  • Surface suggestion: ◇ Alternative: {TOOL} would be {BENEFIT} — install with {COMMAND}
  • Continue without blocking

Critical gap (task extremely tedious with fallback):

  • Surface suggestion: ◆ Caution: {TOOL} recommended for this task — {FALLBACK} will be slow/limited
  • Offer choice: install now, proceed anyway, defer task

Never block on missing tools — graceful degradation always.

Trigger research when:

  • Tool taking 3x+ longer than expected for task size
  • User explicitly asks for better approach
  • Task seems like it should have specialized tool
  • Current tool missing critical feature
  • New tool category needed (not in selection table)

Research workflow:

  1. Search for {TASK} CLI tool 2025 or {TASK} CLI tool 2024
  2. Check GitHub trending in relevant category
  3. Evaluate candidates:
    • Speed: benchmarks vs existing tools
    • Ergonomics: default behavior, output format
    • Maintenance: last commit, issue response time
    • Install: complexity, dependencies
    • Compatibility: OS support, integration

Present findings:

  • Tool name + one-line description
  • Key advantages over current approach
  • Installation command
  • Usage example for current task
  • Trade-offs or caveats

If research yields strong candidate → add to selection table for future reference.

Standard flow:

  1. Receive task → categorize task type (find files, search content, process data)
  2. Check detection → run script if not yet run this session
  3. Select tool → use selection table + detection results
  4. Execute → run command with optimal flags
  5. Evaluate → if slow/frustrating → trigger research

Research flow:

  1. Trigger identified → surface to user with △ This seems slow — research alternatives?
  2. User confirms → web search for modern tools
  3. Evaluate candidates → speed, ergonomics, maintenance
  4. Present findings → tool + advantages + install + example
  5. Update knowledge → add to selection table if strong fit

Scenario: Search for authentication code

Task: Find all files containing "authentication" Detection: rg available Selection: Use rg over grep

bash
rg "authentication" --type ts --type js

Scenario: Find config files

Task: Find all YAML files in project Detection: fd available Selection: Use fd over find

bash
fd -e yaml -e yml

Scenario: Process API response

Task: Extract specific fields from JSON Detection: jq unavailable Fallback: Use node/python Suggestion: ◇ Alternative: jq would simplify this — install with brew install jq

bash
node -e "console.log(JSON.parse(require('fs').readFileSync(0, 'utf-8')).field)"

ALWAYS:

  • Run detection script before recommending specific tools
  • Use selection table to map task to best available tool
  • Provide fallback when suggesting tools that might not be installed
  • Surface suggestions for significant improvements (2x+ better)
  • Trigger research when tool underperforms expectations

NEVER:

  • Assume a tool is installed without checking detection results
  • Block workflow on missing non-essential tools
  • Recommend abandonware or unmaintained tools
  • Use legacy tools when modern alternatives are available
  • Skip fallback strategy when preferred tool missing
  • tool-catalog.md — comprehensive tool documentation
  • alternatives.md — how to research new tools
  • detection-script.md — detection script implementation

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