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.
git clone --depth 1 https://github.com/catlog22/Claude-Code-WorkflowWrote 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.
[](https://agentmods.dev/commands/catlog22/claude-code-workflow/discover-by-prompt)<a href="https://agentmods.dev/commands/catlog22/claude-code-workflow/discover-by-prompt"><img src="https://agentmods.dev/badge/commands/catlog22/claude-code-workflow/discover-by-prompt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/catlog22/claude-code-workflow/discover-by-prompt"><img src="https://agentmods.dev/badge/commands/catlog22/claude-code-workflow/discover-by-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.06389 |
| Opus 5.5 | $0.00017 | $0.02556 |
| Sonnet 5.5 | $0.00009 | $0.01278 |
| Haiku 4.5 | $0.00004 | $0.00639 |
Grade A, and why
issue:discover-by-prompt 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 769 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Mode
When --yes or -y: Auto-continue all iterations, skip confirmations.
Issue Discovery by Prompt
Quick Start
# Discover issues based on user description
/issue:discover-by-prompt "Check if frontend API calls match backend implementations"
# Compare specific modules
/issue:discover-by-prompt "Verify auth flow consistency between mobile and web clients" --scope=src/auth/**,src/mobile/**
# Deep exploration with more iterations
/issue:discover-by-prompt "Find all places where error handling is inconsistent" --depth=deep --max-iterations=8
# Focused backend-frontend contract check
/issue:discover-by-prompt "Compare REST API definitions with frontend fetch calls"
Core Difference from /issue:discover:
discover: Pre-defined perspectives (bug, security, etc.), parallel executiondiscover-by-prompt: User-driven prompt, Gemini-planned strategy, iterative exploration
What & Why
Core Concept
Prompt-driven issue discovery with intelligent planning. Instead of fixed perspectives, this command:
- Analyzes user intent via Gemini to understand what to find
- Plans exploration strategy dynamically based on codebase structure
- Executes iterative multi-agent exploration with feedback loops
- Performs cross-module comparison when detecting comparison intent
Value Proposition
- Natural Language Input: Describe what you want to find, not how to find it
- Intelligent Planning: Gemini designs optimal exploration strategy
- Iterative Refinement: Each round builds on previous discoveries
- Cross-Module Analysis: Compare frontend/backend, mobile/web, old/new implementations
- Adaptive Exploration: Adjusts direction based on findings
Use Cases
| Scenario | Example Prompt |
|---|---|
| API Contract | "Check if frontend calls match backend endpoints" |
| Error Handling | "Find inconsistent error handling patterns" |
| Migration Gap | "Compare old auth with new auth implementation" |
| Feature Parity | "Verify mobile has all web features" |
| Schema Drift | "Check if TypeScript types match API responses" |
| Integration | "Find mismatches between service A and service B" |
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.
- 2mo ago First seen · 769 lines · 43 tokens per session scan A ad6ce6499604
issue:discover-by-prompt is a command published in the GitHub repository catlog22/Claude-Code-Workflow (2,118 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 6,389 once invoked, about $0.0002 per session on Opus 5.5. 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.
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