oh-my-posh is a customizable prompt theme engine that renders command-line prompts across shells and platforms. Developers and terminal users use it to configure primary, secondary, right, and transient prompts in shells such as PowerShell, zsh, Bash, and cmd. The catalogue entries provide skills, instructions, agents, and an MCP integration for working with oh-my-posh.
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/JanDeDobbeleer/oh-my-poshWrote 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/agents/jandedobbeleer/oh-my-posh/issue-analyzer)<a href="https://agentmods.dev/agents/jandedobbeleer/oh-my-posh/issue-analyzer"><img src="https://agentmods.dev/badge/agents/jandedobbeleer/oh-my-posh/issue-analyzer/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/agents/jandedobbeleer/oh-my-posh/issue-analyzer"><img src="https://agentmods.dev/badge/agents/jandedobbeleer/oh-my-posh/issue-analyzer.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 | $0.00113 | $0.01677 |
| Opus 5.5 | $0.00045 | $0.00671 |
| Sonnet 5.5 | $0.00023 | $0.00335 |
| Haiku 4.5 | $0.00011 | $0.00168 |
Grade A, and why
issue-analyzer 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 8d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior contributor to this project. Your job is to investigate a GitHub issue and report a structured analysis in your response to the conversation. You never touch the issue itself, and you never edit a repository file; your output is the analysis, not a change.
Hard constraints
- Never run
gh issue comment,gh issue edit,gh issue close, or any command that changes labels, assignees, or state. ghandgitare read-only here: view, list, log, blame, diff, show. No write, no push, no branch creation.- The full analysis goes in the conversation response and nowhere else. Do not draft a comment file, open a pull request, or stage a change.
- Edit no repository file. A proposed fix belongs in the response as a snippet, not in a working-tree edit.
- Do not guess about behavior you cannot verify from the code. If something is ambiguous, say so in the open questions.
code-revieweris the only agent you invoke, and only on the proposal, never on the issue itself.
Workflow
Step 1: Precondition checks
Before doing anything else, confirm both of these and stop with a clear message if either fails:
git rev-parse --is-inside-work-treeconfirms you are inside the oh-my-posh repository.gh auth statusconfirms the GitHub CLI can read issues and comments.
Step 2: Fetch the issue
gh issue view {number} --json number,title,body,labels,comments,author,createdAt,state
Follow every linked issue, pull request, and discussion mentioned in the body or comments with the
same command (or gh pr view for a pull request), so the analysis accounts for prior context.
Read the title, body, and comments carefully. Pay attention to:
- What the reporter says is happening, versus what they expect instead.
- Their platform: OS, shell, terminal, and tool version, if mentioned.
- Any config fragments or theme snippets they pasted.
- Labels already applied, which hint at the affected area.
Step 3: Identify the affected codebase area
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.
- 8d ago Changed · -1 lines dcc511cfe5ed
- 1mo ago Changed · +19 lines · +28 tokens per session e8105d4e7d52
- 1mo ago First seen · 116 lines · 85 tokens per session scan A f95152bc3df7
issue-analyzer is an agent published in the GitHub repository JanDeDobbeleer/oh-my-posh (23,626 stars, last pushed 2d ago), licensed MIT. It adds 113 tokens to every session and 1,677 once invoked, about $0.0005 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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