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 skills add CodeInfinity1/Stram --skill local-app-troubleshootinggit clone --depth 1 https://github.com/CodeInfinity1/StramWrote 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/skills/codeinfinity1/stram/local-app-troubleshooting)<a href="https://agentmods.dev/skills/codeinfinity1/stram/local-app-troubleshooting"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/local-app-troubleshooting/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/skills/codeinfinity1/stram/local-app-troubleshooting"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/local-app-troubleshooting.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 | $0.00035 | $0.00503 |
| Opus 5.5 | $0.00014 | $0.00201 |
| Sonnet 5.5 | $0.00007 | $0.00101 |
| Haiku 4.5 | $0.00003 | $0.00050 |
Grade A, and why
local-app-troubleshooting 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 1mo 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local App Troubleshooting
Purpose
Help debug local desktop or browser apps by gathering real evidence: running windows, visible UI, local logs/files, browser state, screenshots, and system readiness.
When To Use
Use when an app is frozen, hidden, misconfigured, failing tests, showing errors, not opening, not responding, or behaving differently than expected.
Inputs And Evidence
- App name, window title, error text, expected behavior, and recent actions.
- Window list, UIA observation, screenshot, relevant files/logs, browser session evidence, and system status.
- Reproduction steps and any safe restart/close approval.
Tool Map
system_statusos_windowsactive_windowos_observe_uiscreenshot_captureread_filesearch_workspacebrowser_live_statusbrowser_live_observe
Workflow
- Identify whether the issue is desktop UI, browser UI, service, file/config, or environment.
- Gather current state before attempting fixes.
- Inspect visible errors, logs, and recent app state.
- Form a hypothesis from evidence and choose the next low-risk check.
- Use approval-gated actions for restarts, closing windows, typing, or config changes.
- Verify the app state after the fix or report the blocker.
Native Implementation Boundaries
- Use Stram OS, browser, system, and file tools.
- Do not import Windows-use, browser-use, or external reference troubleshooting code.
- Do not replace diagnosis with keyword-based error matching; reason from evidence.
Safety And Approval
- Do not close unsaved work or restart services without approval.
- Avoid exposing private screen/log data in summaries.
- Keep destructive fixes separate from diagnostic steps.
Verification
- Current state should be proven by tool output.
- Fixes should have a post-action observation or test.
- If a cause is uncertain, label it as a hypothesis.
Failure Modes
- Fixing before observing.
- Restarting away useful error evidence.
- Confusing browser failure with backend/service failure.
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.
- 1mo ago First seen · 71 lines · 35 tokens per session scan A 8a9515cba909
local-app-troubleshooting is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 35 tokens to every session and 503 once invoked, about $0.0001 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 2026-09-03.
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debug
Structured platform troubleshooting — classifies the problem layer, collects evidence, forms a root-cause hypothesis, and proposes a fix with validation and rollback steps.