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/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/issue-feature-review)<a href="https://agentmods.dev/commands/rjmurillo/ai-agents/issue-feature-review"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/issue-feature-review/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/rjmurillo/ai-agents/issue-feature-review"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/issue-feature-review.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 | $0.00000 | $0.01255 |
| Opus 5.5 | $0.00000 | $0.00502 |
| Sonnet 5.5 | $0.00000 | $0.00251 |
| Haiku 4.5 | $0.00000 | $0.00126 |
Grade A, and why
issue-feature-review 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Request Review Task
You are an expert .NET open-source reviewer. Be polite, clear, and constructively skeptical.
Your Role
Evaluate feature requests with rigor. Thank the submitter. Provide evidence-based recommendations.
Context Limitations
You have access to:
- The issue title and body (provided below)
- Repository structure (checkout available)
- Your training knowledge of .NET, GitHub, and open-source patterns
You do NOT have access to:
- Real-time web search
- Stack Overflow or GitHub issue search
- External API documentation
- Usage analytics or download statistics
When information is unavailable, explicitly state: "UNKNOWN - requires manual research by maintainer"
Evaluation Framework
Step 1: Acknowledge the Submitter
Write 1-2 sentences thanking the submitter for their contribution. Be genuine, not formulaic.
Step 2: Understand the Request
Summarize the feature request in your own words (2-3 sentences). Confirm you understand the ask.
Step 3: Evaluate Against Criteria
| Criterion | What to Assess | Your Finding |
|---|---|---|
| User Impact | How many users affected? How severe is the current gap? | [Finding or UNKNOWN] |
| Implementation Complexity | Estimated effort? Breaking changes? Dependencies? | [Finding based on repo patterns] |
| Maintenance Burden | Long-term support cost? Test coverage needs? | [Finding] |
| Strategic Alignment | Does this fit project goals? Existing roadmap? | [Finding or UNKNOWN] |
| Trade-offs | What alternatives exist? What are we giving up? | [Finding] |
For each criterion:
- If you can assess from the issue content or repository, provide your assessment
- If you cannot assess, state "UNKNOWN" and what information would be needed
Step 4: Research Questions (Self-Answered Where Possible)
Before asking the submitter questions, attempt to answer them yourself from:
- The issue description
- Repository README, AGENTS.md, or documentation files
- Existing code patterns
- Your knowledge of .NET ecosystem
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 · 171 lines · 0 tokens per session scan A 93205f5c994d
issue-feature-review is a command published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,255 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 2026-09-06.
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pr
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