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/implementgit clone --depth 1 https://github.com/Hint-Services/mcp-limitlessWhat 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 | $0.00538 |
| Opus 5 | $0.00000 | $0.00269 |
| Sonnet 5 | $0.00000 | $0.00108 |
| Haiku 4.5 | $0.00000 | $0.00054 |
Grade A, and why
implement 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 yesterday.
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 implement — 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 engineer tasked with implementing GitHub issues as code changes. Your goal is to analyze the issue, create a plan, implement the changes, and create a pull request. Follow these steps carefully:
-
Read the GitHub issue: <github_issue> $ARGUMENTS </github_issue>
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Create a new branch associated with the issue. Use the following naming convention: "issue-[issue_number]-[short_description]". For example, "issue-123-add-login-feature".
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Analyze the issue and the associated code in the repository. Ensure you understand the requirements and the existing codebase.
-
Develop a multi-step implementation plan. Each step should be testable. Format your plan as follows: <implementation_plan> Step 1: [Description]
- Test: [How to test this step]
Step 2: [Description]
- Test: [How to test this step]
... </implementation_plan>
-
For each step in your implementation plan: a. Describe the code changes you would make. b. Explain how to test the changes. c. Ask for user approval before proceeding to the next step.
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After implementing all steps, review the changes and identify potential refactors. Present these refactors to the user for approval: <refactor_suggestions> Refactor 1: [Description] Refactor 2: [Description] ... </refactor_suggestions>
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Implement approved refactors.
-
Create a pull request associated with the GitHub issue. Include: a. A clear title summarizing the changes b. A description of the changes made c. Any testing instructions d. Reference to the original issue
Your final output should include:
- The new branch name
- The implementation plan
- A summary of the changes made
- Refactor suggestions (if any)
- Pull request details
Format your final output as follows: <ai_engineer_output> <branch_name>[Branch name]</branch_name>
<implementation_plan> [Your implementation plan] </implementation_plan>
<changes_summary> [Summary of changes made] </changes_summary>
<refactor_suggestions> [Refactor suggestions, if any] </refactor_suggestions>
<pull_request> Title: [Pull request title] Description: [Pull request description] Testing Instructions: [Testing instructions] Related Issue: [Link to the original issue] </pull_request> </ai_engineer_output>
Remember to wait for user approval at each step of the implementation process and before making any refactors.
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.
- yesterday First seen · 78 lines · 0 tokens per session scan A 3a15a914d0f1
implement 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 538 tokens. A static security scan graded it A with 0 findings. It is 100% identical to implement, 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.
constitution
Create or update the project constitution from interactive or provided principle inputs.