A coding command that turns a GitHub issue into planned code changes and a pull request. GitHub issues are written tasks or bug reports attached to a repository.

Use it to analyse an issue, create a matching branch, plan and implement the changes, test each step, and prepare a pull request.

It gives the work a defined path from understanding the request through implementation and review. Each planned step includes a way to test it, with approval requested before continuing.

How Geralt1983/mcp-todoist configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to Geralt1983/mcp-todoist. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/Geralt1983/mcp-todoist/main/.claude/commands/implement.md

Clone the repo

git clone --depth 1 https://github.com/Geralt1983/mcp-todoist

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/geralt1983/mcp-todoist/implement/github.svg)](https://agentmods.dev/commands/geralt1983/mcp-todoist/implement)

Your own site

<a href="https://agentmods.dev/commands/geralt1983/mcp-todoist/implement"><img src="https://agentmods.dev/badge/commands/geralt1983/mcp-todoist/implement/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/geralt1983/mcp-todoist/implement"><img src="https://agentmods.dev/badge/commands/geralt1983/mcp-todoist/implement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 538 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 100% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00538
Opus 5.5	$0.00000	$0.00215
Sonnet 5.5	$0.00000	$0.00108
Haiku 4.5	$0.00000	$0.00054

Measured 2mo ago against content hash 3a15a914d0f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

Origin

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.

.claude/commands/implement.md · 78 lines

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>
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".
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.
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>
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.

Changes

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.

2mo ago First seen · 78 lines · 0 tokens per session scan A 3a15a914d0f1

Subscribe to this mod's changes

implement is a command published in the GitHub repository Geralt1983/mcp-todoist (0 stars, last pushed 11mo 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.

Git and workflow Planning

implement next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
implementGeralt1983/mcp-todoist	Command	0	11mo ago	MIT	A	0	Claude Code
merge-conflict-analysisrjmurillo/ai-agents	Command	49	yesterday	MIT	A	0	GitHub Copilot
release-notesOpenHands/extensions	Command	176	yesterday	MIT	A	44	Claude Code
commitechoVic/blade-code	Command	181	24d ago	MIT	A	8	Claude Code
repo-audittractorjuice/arc-kit	Command	2.3k	2d ago	none	A	29	Claude Code
propsmill/infrahub-mcp	Command	10	yesterday	Apache-2.0	A	18	Claude Code
codex-reviewoalders/kitchen-sink	Command	5	4d ago	MIT	A	41	Claude Code

mcp-todoist: Command for Claude Code