search-router

parcadei/continuous-claude-v3 · updated Apr 8, 2026

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$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill search-router
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summary

Use the most token-efficient search tool for each query type.

skill.md

Search Tool Router

Use the most token-efficient search tool for each query type.

When to Use

  • Searching for code patterns
  • Finding where something is implemented
  • Looking for specific identifiers
  • Understanding how code works

Decision Tree

Query Type?
├── CODE EXPLORATION (symbols, call chains, data flow)
│   → TLDR Search - 95% token savings
│   DEFAULT FOR ALL CODE SEARCH - use instead of Grep
│   Examples: "spawn_agent", "DataPoller", "redis usage"
│   Command: tldr search "query" .
├── STRUCTURAL (AST patterns)
│   → AST-grep (/ast-grep-find) - ~50 tokens output
│   Examples: "def foo", "class Bar", "import X", "@decorator"
├── SEMANTIC (conceptual questions)
│   → TLDR Semantic - 5-layer embeddings (P6)
│   Examples: "how does auth work", "find error handling patterns"
│   Command: tldr semantic search "query"
├── LITERAL (exact text, regex)
│   → Grep tool - LAST RESORT
│   Only when TLDR/AST-grep don't apply
│   Examples: error messages, config values, non-code text
└── FULL CONTEXT (need complete understanding)
    → Read tool - 1500+ tokens
    Last resort after finding the right file

Token Efficiency Comparison

Tool Output Size Best For
TLDR ~50-500 DEFAULT: Code symbols, call graphs, data flow
TLDR Semantic ~100-300 Conceptual queries (P6, embedding-based)
AST-grep ~50 tokens Function/class definitions, imports, decorators
Grep ~200-2000 LAST RESORT: Non-code text, regex
Read ~1500+ Full understanding after finding the file

Examples

# CODE EXPLORATION → TLDR (DEFAULT)
tldr search "spawn_agent" .
tldr search "redis" . --layer call_graph

# STRUCTURAL → AST-grep
/ast-grep-find "async def $FUNC($$$):" --lang python

# SEMANTIC → TLDR Semantic
tldr semantic search "how does authentication work"

# LITERAL → Grep (LAST RESORT - prefer TLDR)
Grep pattern="check_evocation" path=opc/scripts

# FULL CONTEXT → Read (after finding file)
Read file_path=opc/scripts/z3_erotetic.py

Optimal Flow

1. AST-grep: "Find async functions" → 3 file:line matches
2. Read: Top match only → Full understanding
3. Skip: 4 irrelevant files → 6000 tokens saved

Related Skills

  • /tldr-search - DEFAULT - Code exploration with 95% token savings
  • /ast-grep-find - Structural code search
  • /morph-search - Fast text search
how to use search-router

How to use search-router on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add search-router
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill search-router

The skills CLI fetches search-router from GitHub repository parcadei/continuous-claude-v3 and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/search-router

Reload or restart Cursor to activate search-router. Access the skill through slash commands (e.g., /search-router) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.732 reviews
  • Ama Shah· Dec 20, 2024

    Solid pick for teams standardizing on skills: search-router is focused, and the summary matches what you get after install.

  • Ren Anderson· Dec 8, 2024

    Registry listing for search-router matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sofia Sethi· Nov 27, 2024

    search-router reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Rahul Santra· Nov 15, 2024

    search-router fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Omar Jackson· Nov 11, 2024

    I recommend search-router for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Isabella Khan· Nov 3, 2024

    search-router is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Lucas Reddy· Oct 22, 2024

    Solid pick for teams standardizing on skills: search-router is focused, and the summary matches what you get after install.

  • Sofia Malhotra· Oct 18, 2024

    We added search-router from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Pratham Ware· Oct 6, 2024

    search-router has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Omar Patel· Oct 2, 2024

    Keeps context tight: search-router is the kind of skill you can hand to a new teammate without a long onboarding doc.

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