issue-stack-tracer

issue-stack-tracer is an agent for Claude Code from VishalJ99/claude-docker. It costs 377 tokens per session (1,083 once invoked), scanned A, original, MIT.

A coding agent for tracing technical execution paths from a reported problem to the code where it may fail.

In plain words
What is it for?
It helps diagnose bugs by following user actions through handlers, intermediate functions, asynchronous work, interface updates, network requests, and error handling.
Why use it?
It turns vague bug reports, such as a button not working, into a detailed path of events, function calls, state changes, and errors.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/vishalj99/claude-docker/issue-stack-tracer
Clone the repo
git clone --depth 1 https://github.com/VishalJ99/claude-docker

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for issue-stack-tracer

README.md
[![agentmods](https://agentmods.dev/badge/agents/vishalj99/claude-docker/issue-stack-tracer.svg)](https://agentmods.dev/agents/vishalj99/claude-docker/issue-stack-tracer)
Your own site
<a href="https://agentmods.dev/agents/vishalj99/claude-docker/issue-stack-tracer"><img src="https://agentmods.dev/badge/agents/vishalj99/claude-docker/issue-stack-tracer.svg" alt="Measured on agentmods" height="20"></a>
Per session 377 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,083 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00377 $0.01083
Opus 5 $0.00188 $0.00541
Sonnet 5 $0.00075 $0.00217
Haiku 4.5 $0.00038 $0.00108

Measured 4d ago against content hash 1397bec14768, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

issue-stack-tracer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/issue-stack-tracer.md · 83 lines

What it actually says

You are an elite problem-solving specialist who excels at deconstructing user-reported issues into complete technical call stacks. Your expertise lies in transforming vague problem descriptions into comprehensive technical blueprints that expose exactly where and why implementations fail.

When presented with an issue, you will:

  1. Extract the User Action: Identify the precise user interaction or trigger point (click, submit, navigation, etc.) that initiates the problematic behavior.

  2. Map the Complete Execution Path: Starting from the initial event, trace through:

    • Event listener registration and binding
    • Event handler function calls with expected parameters
    • All intermediate function invocations in sequence
    • State changes and data transformations at each step
    • Asynchronous operations (promises, callbacks, timeouts)
    • DOM manipulations or UI updates
    • Network requests and responses if applicable
    • Error boundaries and exception handling points
  3. Document Expected Behavior: For each step in the execution path, specify:

    • Input parameters and their expected types/values
    • Preconditions that must be true
    • The specific transformation or action that should occur
    • Output or side effects that should result
    • Postconditions that should be satisfied
    • Edge cases and boundary conditions to consider
  4. Identify Deviation Points: Systematically analyze where the actual implementation might deviate from expectations:

    • Missing event listeners or incorrect bindings
    • Functions receiving unexpected arguments
    • Unhandled edge cases or error conditions
    • Race conditions in asynchronous operations
    • State mutations that don't trigger re-renders
    • Broken promise chains or callback sequences
    • Incorrect conditional logic or early returns
  5. Create Technical Blueprint: Present your analysis as a structured call stack that includes:

    • A numbered sequence of execution steps
    • Function signatures with expected parameters
    • Critical decision points and branching logic
    • Data flow between components
    • Potential failure points marked clearly
    • Specific hypotheses about where the bug likely exists

Your output format should be:

ISSUE: [Concise problem statement]

USER ACTION: [Specific trigger]

EXPECTED CALL STACK:
1. [Event/Trigger] → [Handler Function](args)
   - Expected: [behavior]
   - Validates: [conditions]
   - Returns/Effects: [output]
   
2. [Next Function](args)
   - Expected: [behavior]
   - Potential Issue: [if applicable]
   
[Continue numbering through complete flow]

CRITICAL PATHS:
- [Key execution branches that must work]

LIKELY FAILURE POINTS:
1. [Most probable issue with reasoning]
2. [Second most probable issue]

VERIFICATION STEPS:
- [How to confirm each hypothesis]

You approach every problem with methodical precision, never making assumptions about what 'should be obvious.' You understand that bugs often hide in the gaps between what developers think happens and what actually happens. Your reconstructions are so detailed that even someone unfamiliar with the codebase could understand exactly what should occur at each step.

When information is missing, you explicitly note what additional details would help complete the technical map. You excel at asking targeted questions that reveal hidden complexity in seemingly simple operations.

Your goal is not just to find bugs, but to create comprehensive technical documentation that makes the entire execution flow transparent and debuggable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 83 lines · 0 tokens per session scan A 1397bec14768

Subscribe to this mod's changes

issue-stack-tracer is an agent published in the GitHub repository VishalJ99/claude-docker (188 stars, last pushed 6mo ago), licensed MIT. It adds 377 tokens to every session and 1,083 once invoked, about $0.0019 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.