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/hint-services/mcp-limitless/issuesgit clone --depth 1 https://github.com/Hint-Services/mcp-limitlessWrote 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/hint-services/mcp-limitless/issues)<a href="https://agentmods.dev/commands/hint-services/mcp-limitless/issues"><img src="https://agentmods.dev/badge/commands/hint-services/mcp-limitless/issues.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00510 |
| Opus 5 | $0.00000 | $0.00255 |
| Sonnet 5 | $0.00000 | $0.00102 |
| Haiku 4.5 | $0.00000 | $0.00051 |
Grade A, and why
issues scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to issues — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You are an AI assistant tasked with creating well‑structured GitHub issues for feature requests, bug reports, or improvement ideas. Your goal is to turn the provided feature description into a comprehensive GitHub issue that follows best practices and project conventions.
First, you will be given a feature description and a repository URL. Here they are:
<feature_description> #$ARGUMENTS </feature_description>
Follow these steps to complete the task, make a todo list and think ultrahard:
-
Research the repository:
- Visit the provided repo_url and examine the repository’s structure, existing issues, and documentation.
- Look for any CONTRIBUTING.md, ISSUE_TEMPLATE.md, or similar files that might contain guidelines for creating issues.
- Note the project’s coding style, naming conventions, and any specific requirements for submitting issues.
-
Research best practices:
- Search for current best practices in writing GitHub issues, focusing on clarity, completeness, and actionability.
- Look for examples of well‑written issues in popular open‑source projects for inspiration.
-
Present a plan:
- Based on your research, outline a plan for creating the GitHub issue.
- Include the proposed structure of the issue, any labels or milestones you plan to use, and how you’ll incorporate project‑specific conventions.
- Present this plan in tags.
-
Create the GitHub issue:
- Once the plan is approved, draft the GitHub issue content.
- Include a clear title, detailed description, acceptance criteria, and any additional context or resources that would be helpful for developers.
- Use appropriate formatting (e.g., Markdown) to enhance readability.
- Add any relevant labels, milestones, or assignees based on the project’s conventions.
-
Final output:
- Present the complete GitHub issue content in <github_issue> tags.
- Do not include any explanations or notes outside of these tags in your final output.
Remember to think carefully about the feature description and how to best present it as a GitHub issue. Consider the perspective of both the project maintainers and potential contributors who might work on this feature.
Your final output should consist of only the content within the <github_issue> tags, ready to be copied and pasted directly into GitHub. Make sure to use the GitHub CLI gh issue create to create the actual issue after you generate. Assign either the label bug or enhancement based on the nature of the issue.
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.
- 3d ago First seen · 43 lines · 0 tokens per session scan A 801ed951a691
issues is a command published in the GitHub repository Hint-Services/mcp-limitless (1 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 510 tokens. A static security scan graded it A with 0 findings. It is 100% identical to issues, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.