grepai-trace-callees▌
yoanbernabeu/grepai-skills · updated Apr 8, 2026
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This skill covers using grepai trace callees to find all functions called by a specific function.
GrepAI Trace Callees
This skill covers using grepai trace callees to find all functions called by a specific function.
When to Use This Skill
- Understanding function dependencies
- Mapping function behavior
- Finding deeply nested dependencies
- Code comprehension and documentation
What is Trace Callees?
grepai trace callees answers: "What does this function call?"
func ProcessOrder(order) {
validateOrder(order)
calculateTotal(order)
sendConfirmation(order.email)
}
│
↓
┌───────┴───────────────────┐
│ What does ProcessOrder │
│ call? │
├───────────────────────────┤
│ • validateOrder │
│ • calculateTotal │
│ • sendConfirmation │
└───────────────────────────┘
Basic Usage
grepai trace callees "FunctionName"
Example
grepai trace callees "ProcessOrder"
Output:
🔍 Callees of "ProcessOrder"
Found 4 callees:
1. validateOrder
File: services/order.go:45
Context: validateOrder(order)
2. calculateTotal
File: services/order.go:48
Context: total := calculateTotal(order.Items)
3. applyDiscount
File: services/order.go:51
Context: total = applyDiscount(total, order.Coupon)
4. sendConfirmation
File: services/order.go:55
Context: sendConfirmation(order.Email, total)
JSON Output
grepai trace callees "ProcessOrder" --json
Output:
{
"query": "ProcessOrder",
"mode": "callees",
"count": 4,
"results": [
{
"file": "services/order.go",
"line": 45,
"callee": "validateOrder",
"context": "validateOrder(order)"
},
{
"file": "services/order.go",
"line": 48,
"callee": "calculateTotal",
"context": "total := calculateTotal(order.Items)"
},
{
"file": "services/order.go",
"line": 51,
"callee": "applyDiscount",
"context": "total = applyDiscount(total, order.Coupon)"
},
{
"file": "services/order.go",
"line": 55,
"callee": "sendConfirmation",
"context": "sendConfirmation(order.Email, total)"
}
]
}
Compact JSON (AI Optimized)
grepai trace callees "ProcessOrder" --json --compact
Output:
{
"q": "ProcessOrder",
"m": "callees",
"c": 4,
"r": [
{"f": "services/order.go", "l": 45, "fn": "validateOrder"},
{"f": "services/order.go", "l": 48, "fn": "calculateTotal"},
{"f": "services/order.go", "l": 51, "fn": "applyDiscount"},
{"f": "services/order.go", "l": 55, "fn": "sendConfirmation"}
]
}
TOON Output (v0.26.0+)
TOON format offers ~50% fewer tokens than JSON:
grepai trace callees "ProcessOrder" --toon
Note:
--jsonand--toonare mutually exclusive.
Extraction Modes
Fast Mode (Default)
grepai trace callees "ProcessOrder" --mode fast
Precise Mode
grepai trace callees "ProcessOrder" --mode precise
| Mode | Speed | Accuracy | Dependencies |
|---|---|---|---|
fast |
⚡⚡⚡ | Good | None |
precise |
⚡⚡ | Excellent | tree-sitter |
Use Cases
Understanding Function Behavior
# What does this complex function do?
grepai trace callees "handleRequest"
# Map the data flow
grepai trace callees "processPayment"
Finding Dependencies
# What external services does this call?
grepai trace callees "syncData"
# What database operations happen?
grepai trace callees "saveUser"
Code Review
# What side effects does this function have?
grepai trace callees "updateProfile"
# Is this function doing too much?
grepai trace callees "doEverything" # Lots of callees = code smell
Documentation
# Generate dependency list for docs
grepai trace callees "initialize" --json | jq '.results[].callee'
Callers vs Callees
| Command | Question | Use Case |
|---|---|---|
trace callers |
Who calls me? | Impact analysis |
trace callees |
What do I call? | Behavior analysis |
# Combined analysis
grepai trace callers "processOrder" # Who uses this?
grepai trace callees "processOrder" # What does it do?
Filtering Results
By File Type
# Get callees and filter to only .go files
grepai trace callees "main" --json | jq '.results[] | select(.file | endswith(".go"))'
Exclude Test Functions
grepai trace callees "Login" --json | jq '.results[] | select(.callee | startswith("Test") | not)'
Count by Category
# Count how many database vs. API calls
grepai trace callees "processOrder" --json | jq '.results[].callee' | grep -c "db"
What Callees Includes
The trace finds:
- Direct function calls
- Method calls
- Built-in function calls (depending on mode)
Example
func ProcessOrder(order Order) error {
// Direct call
validateOrder(order)
// Method call
order.Validate()
// Package function
utils.Log("processing")
// Built-in (may or may not be captured)
fmt.Println("done")
return nil
}
Callees found:
validateOrderValidate(method)Log(from utils)Println(depending on mode)
Limitations
What Callees Might Miss
- Dynamic/runtime calls
- Callbacks and closures
- Interface method calls (may show interface, not implementation)
- Reflection-based calls
Example of Undetected Call
func process(fn func()) {
fn() // Callee is unknown at static analysis time
}
Combining with Trace Graph
For recursive dependency analysis, use trace graph:
# Direct callees only
grepai trace callees "main"
# Full dependency tree (recursive)
grepai trace graph "main" --depth 3
Scripting Examples
List All Callees
grepai trace callees "main" --json | jq -r '.results[].callee' | sort -u
Check for Specific Callee
# Does processOrder call sendEmail?
grepai trace callees "processOrder" --json | jq -e '.results[] | select(.callee == "sendEmail")' && echo "Yes" || echo "No"
Generate Dependency Report
#!/bin/bash
echo "# Function Dependencies Report"
echo ""
for fn in main initialize processOrder; do
how to use grepai-trace-calleesHow to use grepai-trace-callees on Cursor
AI-first code editor with Composer
1Prerequisites
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 grepai-trace-callees
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-trace-calleesThe skills CLI fetches grepai-trace-callees from GitHub repository yoanbernabeu/grepai-skills and configures it for Cursor.
3Select 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│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/grepai-trace-calleesReload or restart Cursor to activate grepai-trace-callees. Access the skill through slash commands (e.g., /grepai-trace-callees) 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.
Additional Resources
List & Monetize Your Skill
Submit your Claude Code skill and start earning
GET_STARTED →Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
✓Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
✓Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
✓Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
general reviewsRatings
4.7★★★★★72 reviews- ★★★★★Zara Sanchez· Dec 28, 2024
grepai-trace-callees is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Soo Liu· Dec 16, 2024
Useful defaults in grepai-trace-callees — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kofi Abbas· Dec 12, 2024
Solid pick for teams standardizing on skills: grepai-trace-callees is focused, and the summary matches what you get after install.
- ★★★★★Lucas Chawla· Dec 12, 2024
grepai-trace-callees fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Rahul Santra· Nov 19, 2024
Keeps context tight: grepai-trace-callees is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Mia Gupta· Nov 19, 2024
Useful defaults in grepai-trace-callees — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Arjun Choi· Nov 7, 2024
grepai-trace-callees is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Lucas Bhatia· Nov 3, 2024
grepai-trace-callees has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Arjun Kim· Nov 3, 2024
I recommend grepai-trace-callees for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Arjun Robinson· Oct 26, 2024
grepai-trace-callees reduced setup friction for our internal harness; good balance of opinion and flexibility.
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