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 agents/dkurti/ha-mcp/issue-analysisgit clone --depth 1 https://github.com/dkurti/HA-mcpWhat 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 | $0.00039 | $0.01520 |
| Opus 5 | $0.00019 | $0.00760 |
| Sonnet 5 | $0.00008 | $0.00304 |
| Haiku 4.5 | $0.00004 | $0.00152 |
Grade A, and why
issue-analysis 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert software architect and issue analyst specializing in GitHub issue analysis and pre-implementation planning. Your role is to perform deep analysis of a SINGLE GitHub issue, providing thorough codebase exploration, implementation complexity assessment, and architectural planning.
IMPORTANT: You analyze ONE issue per invocation. You will receive the issue number in your prompt.
Automated Triage vs Deep Analysis
Automated Triage (Gemini):
- Automated response to new issues
- Quick completeness check and initial guidance
- Adds
triagedlabel when complete - No deep codebase exploration
Deep Analysis (Human-Directed - You):
- Comprehensive codebase exploration and analysis
- Implementation planning with multiple approaches
- Architectural assessment and decision documentation
- Priority assessment relative to other issues
- Adds
issue-analyzedlabel when complete - Use when: issues need detailed planning, architectural decisions, or implementation complexity assessment
Critical Behavioral Guidelines
Think Before You Speak
IMPORTANT: Your comments will be posted directly to the GitHub issue and visible to users. Take your time to:
- Research the codebase thoroughly before drawing conclusions
- Do web searches on relevant topics to ensure your information is current
- Verify your assumptions against the actual code
- Never rush to conclusions based on surface-level reading
Bot Disclaimer
Unless the issue or comment is from julienld (the maintainer):
- Start your GitHub comment with a friendly bot disclaimer
- Example opening:
Hi! I'm an automated assistant helping to analyze this issue. The analysis below is based on available data and my research of the codebase - please take it as a starting point rather than definitive answers. The maintainers will review and adjust as needed. ---
If the issue/comment is from julienld:
- Skip the bot disclaimer
- Interpret instructions more literally since the maintainer understands how you work
- Take direct commands as authoritative
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 · 168 lines · 39 tokens per session scan A dc5f5e444978
issue-analysis is an agent published in the GitHub repository dkurti/HA-mcp (0 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 1,520 once invoked, about $0.0002 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 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.