codebase-search

supercent-io/skills-template · updated Apr 30, 2026

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$npx skills add https://github.com/supercent-io/skills-template --skill codebase-search
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summary

Search and navigate large codebases with semantic search, grep patterns, and file discovery.

  • Supports three search modes: semantic search for conceptual queries, grep for exact text and regex patterns, and glob for file discovery by type or naming convention
  • Includes workflow guidance for common scenarios like tracing function calls, understanding feature implementations, locating bugs, and performing impact analysis
  • Provides language-specific patterns for Python, JavaScript, TypeScr
skill.md

Codebase Search

When to use this skill

  • Finding specific functions or classes
  • Tracing function calls and dependencies
  • Understanding code structure and architecture
  • Finding usage examples
  • Identifying code patterns
  • Locating bugs or issues
  • Code archaeology (understanding legacy code)
  • Impact analysis before changes

Instructions

Step 1: Understand what you're looking for

Feature implementation:

  • Where is feature X implemented?
  • How does feature Y work?
  • What files are involved in feature Z?

Bug location:

  • Where is this error coming from?
  • What code handles this case?
  • Where is this data being modified?

API usage:

  • How is this API used?
  • Where is this function called?
  • What are examples of using this?

Configuration:

  • Where are settings defined?
  • How is this configured?
  • What are the config options?

Step 2: Choose search strategy

Semantic search (for conceptual questions):

Use when: You understand what you're looking for conceptually
Examples:
- "How do we handle user authentication?"
- "Where is email validation implemented?"
- "How do we connect to the database?"

Benefits:
- Finds relevant code by meaning
- Works with unfamiliar codebases
- Good for exploratory searches

Grep (for exact text/patterns):

Use when: You know exact text or patterns
Examples:
- Function names: "def authenticate"
- Class names: "class UserManager"
- Error messages: "Invalid credentials"
- Specific strings: "API_KEY"

Benefits:
- Fast and precise
- Works with regex patterns
- Good for known terms

Glob (for file discovery):

Use when: You need to find files by pattern
Examples:
- "**/*.test.js" (all test files)
- "**/config*.yaml" (config files)
- "src/**/*Controller.py" (controllers)

Benefits:
- Quickly find files by type
- Discover file structure
- Locate related files

Step 3: Search workflow

1. Start broad, then narrow:

Step 1: Semantic search "How does authentication work?"
Result: Points to auth/ directory

Step 2: Grep in auth/ for specific function
Pattern: "def verify_token"
Result: Found in auth/jwt.py

Step 3: Read the file
File: auth/jwt.py
Result: Understand implementation

2. Use directory targeting:

# Start without target (search everywhere)
Query: "Where is user login implemented?"
Target: []

# Refine with specific directory
Query: "Where is login validated?"
Target: ["backend/auth/"]

3. Combine searches:

# Find where feature is implemented
Semantic: "user registration flow"

# Find all files involved
Grep: "def register_user"

# Find test files
Glob: "**/*register*test*.py"

# Understand the implementation
Read: registration.py, test_registration.py

Step 4: Common search patterns

Find function definition:

# Python
grep -n "def function_name" --type py

# JavaScript
grep -n "function functionName" --type js
grep -n "const functionName = " --type js

# TypeScript
grep -n "function functionName" --type ts
grep -n "export const functionName" --type ts

# Go
grep -n "func functionName" --type go

# Java
grep -n "public.*functionName" --type java

Find class definition:

# Python
grep -n "class ClassName" --type py

# JavaScript/TypeScript
grep -n "class ClassName" --type js,ts

# Java
grep -n "public class ClassName" --type java

# C++
grep -n "class ClassName" --type cpp

Find class/function usage:

# Python
grep -n "ClassName(" --type py
grep -n "function_name(" --type py

# JavaScript
grep -n "new ClassName" --type js
grep -n "functionName(" --type js

Find imports/requires:

# Python
grep -n "from.*import.*ModuleName" --type py
grep -n "import.*ModuleName" --type py

# JavaScript
grep -n "import.*from.*module-name" --type js
grep -n "require.*module-name" --type js

# Go
grep -n "import.*package-name" --type go

Find configuration:

# Config files
glob "**/*config*.{json,yaml,yml,toml,ini}"

# Environment variables
grep -n "process\\.env\\." --type js
grep -n "os\\.environ" --type py

# Constants
grep -n "^[A-Z_]+\\s*=" --type py
grep -n "const [A-Z_]+" --type js

Find TODO/FIXME:

grep -n "TODO|FIXME|HACK|XXX" -i

Find error handling:

# Python
grep -n "try:|except|raise" --type py

# JavaScript
grep -n "try|catch|throw" --type js

# Go
grep -n "if err != nil" --type go

Step 5: Advanced techniques

Trace data flow:

1. Find where data is created
   Semantic: "Where is user object created?"

2. Search for variable usage
   Grep: "user\\." with context lines

3. Follow transformations
   Read: Files that modify user

4. Find where it's consumed
   Grep: "user\\." in relevant files

Find all callsites of a function:

1. Find function definition
   Grep: "def process_payment"
   Result: payments/processor.py:45

2. Find all imports of that module
   Grep: "from payments.processor import"
   Result: Multiple files

3. Find all calls to the function
   Grep: "process_payment\\("
   Result: All callsites

4. Read each callsite for context
   Read: Each file with context

Understand a feature end-to-end:

1. Find API endpoint
   Semantic: "Where is user registration endpoint?"
   Result: routes/auth.py

2. Trace to controller
   Read: routes/auth.py
   Find: Calls to AuthController.register

3. Trace to service
   Read: controllers/auth.py
   Find: Calls to UserService.create_user

4. Trace to database
   Read: services/user.py
   Find: Database operations

5. Find tests
   Glob: "**/*auth*test*.py"
   Read: Test files for examples

Find related files:

1. Start with known file
   Example: models/user.py

2. Find imports of this file
   Grep: "from models.user import"

3. Find files this imports
   Read: models/user.py
   Note: Import statements

4. Build dependency graph
   Map: All related files

Impact analysis:

Before changing function X:

1. Find all callsites
   Grep: "function_name\\("

2. Find all tests
   Grep: "test.*function_name" -i

3. Check related functionality
   Semantic: "What depends on X?"

4. Review each usage
   Read: Each file using function

5. Plan changes
   Document: Impact and required updates

Step 6: Search optimization

Use appropriate context:

# See surrounding context
grep -n "pattern" -C 5  # 5 lines before and after
grep -n "pattern" -B 3  # 3 lines before
grep -n "pattern" -A 3  # 3 lines after

Case sensitivity:

# Case insensitive
grep -n "pattern" -i

# Case sensitive (default)
grep -n "Pattern"

File type filtering:

# Specific type
grep -n "pattern" --type py

# Multiple types
grep -n "pattern" --type py,js,ts

# Exclude types
grep -n "pattern" --glob "!*.test.js"

Regex patterns:

# Any character: .
grep -n "function.*Name"

# Start of line: ^
grep -n "^class"

# End of line: $
grep -n "TODO$"

# Optional: ?
grep -n "function_name
how to use codebase-search

How to use codebase-search 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 codebase-search
2

Execute installation command

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

$npx skills add https://github.com/supercent-io/skills-template --skill codebase-search

The skills CLI fetches codebase-search from GitHub repository supercent-io/skills-template 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/codebase-search

Reload or restart Cursor to activate codebase-search. Access the skill through slash commands (e.g., /codebase-search) 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.

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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

4.626 reviews
  • Chen Nasser· Sep 21, 2024

    Useful defaults in codebase-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Oshnikdeep· Sep 17, 2024

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

  • Arya Menon· Sep 9, 2024

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

  • Kofi Malhotra· Aug 28, 2024

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

  • Naina Flores· Aug 12, 2024

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

  • Ganesh Mohane· Aug 8, 2024

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

  • Sakshi Patil· Jul 27, 2024

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

  • Isabella Anderson· Jul 19, 2024

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

  • Amelia Taylor· Jul 11, 2024

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

  • Amelia Abebe· Jul 3, 2024

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

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