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.
npx agentmods add commands/dmzoneill/redhat-ai-workflow/debug-prodgit clone --depth 1 https://github.com/dmzoneill/redhat-ai-workflowWhat 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 | $0.00000 | $0.00778 |
| Opus 5 | $0.00000 | $0.00389 |
| Sonnet 5 | $0.00000 | $0.00156 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
debug-prod 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 2d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/debug-prod
Deep investigation of production issues.
Overview
Deep investigation of production issues.
Underlying Skill: debug_prod
This command is a wrapper that calls the debug_prod skill. For detailed process information, see skills/debug_prod.md.
Arguments
| Argument | Required | Description |
|---|---|---|
pod_filter |
No | - |
Usage
Examples
skill_run("debug_prod")
# General production health check
skill_run("debug_prod")
# Investigate specific pod type
skill_run("debug_prod", '{"pod_filter": "processor"}')
# Look at longer time range
skill_run("debug_prod", '{"time_range": "6h"}')
# Investigate specific alert
skill_run("debug_prod", '{"alert_name": "HighErrorRate"}')
# Check stage instead
skill_run("debug_prod", '{"namespace": "tower-analytics-stage"}')
Process Flow
This command invokes the debug_prod skill. The process flow is:
flowchart LR
START([User runs /debug-prod]) --> VALIDATE[Validate Arguments]
VALIDATE --> CALL[Call debug_prod skill]
CALL --> EXECUTE[Execute Skill Steps]
EXECUTE --> RESULT[Return Result]
RESULT --> END([Complete])
style START fill:#6366f1,stroke:#4f46e5,color:#fff
style END fill:#10b981,stroke:#059669,color:#fff
style CALL fill:#3b82f6,stroke:#2563eb,color:#fff
```text
For detailed step-by-step process, see the [debug_prod skill documentation](../skills/debug_prod.md).
## Details
## Instructions
```text
skill_run("debug_prod")
Options
| Parameter | Description | Default |
|---|---|---|
namespace |
Kubernetes namespace | tower-analytics-prod |
alert_name |
Specific alert to investigate | All |
pod_filter |
Filter pods by name pattern | All pods |
time_range |
Log time range | 1h |
Additional Examples
# General production health check
skill_run("debug_prod")
# Investigate specific pod type
skill_run("debug_prod", '{"pod_filter": "processor"}')
# Look at longer time range
skill_run("debug_prod", '{"time_range": "6h"}')
# Investigate specific alert
skill_run("debug_prod", '{"alert_name": "HighErrorRate"}')
# Check stage instead
skill_run("debug_prod", '{"namespace": "tower-analytics-stage"}')
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.
- 2d ago First seen · 138 lines · 0 tokens per session scan A e01c1f06fb81
debug-prod is a command published in the GitHub repository dmzoneill/redhat-ai-workflow (5 stars, last pushed 23d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 778 tokens. 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 2026-08-31.
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