Borrowing it
Nothing to install: this file belongs to julianobarbosa/azure-finops-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/julianobarbosa/azure-finops-mcp-server/main/.claude/commands/BMad/tasks/execute-checklist.mdgit clone --depth 1 https://github.com/julianobarbosa/azure-finops-mcp-serverWrote 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/julianobarbosa/azure-finops-mcp-server/execute-checklist)<a href="https://agentmods.dev/commands/julianobarbosa/azure-finops-mcp-server/execute-checklist"><img src="https://agentmods.dev/badge/commands/julianobarbosa/azure-finops-mcp-server/execute-checklist/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/julianobarbosa/azure-finops-mcp-server/execute-checklist"><img src="https://agentmods.dev/badge/commands/julianobarbosa/azure-finops-mcp-server/execute-checklist.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 | $0.00834 |
| Opus 5 | $0.00000 | $0.00417 |
| Sonnet 5 | $0.00000 | $0.00167 |
| Haiku 4.5 | $0.00000 | $0.00083 |
Grade A, and why
execute-checklist 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 9d 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
94% identical to execute-checklist — 2 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/execute-checklist Task
When this command is used, execute the following task:
Checklist Validation Task
This task provides instructions for validating documentation against checklists. The agent MUST follow these instructions to ensure thorough and systematic validation of documents.
Available Checklists
If the user asks or does not specify a specific checklist, list the checklists available to the agent persona. If the task is being run not with a specific agent, tell the user to check the .bmad-core/checklists folder to select the appropriate one to run.
Instructions
-
Initial Assessment
- If user or the task being run provides a checklist name:
- Try fuzzy matching (e.g. "architecture checklist" -> "architect-checklist")
- If multiple matches found, ask user to clarify
- Load the appropriate checklist from .bmad-core/checklists/
- If no checklist specified:
- Ask the user which checklist they want to use
- Present the available options from the files in the checklists folder
- Confirm if they want to work through the checklist:
- Section by section (interactive mode - very time consuming)
- All at once (YOLO mode - recommended for checklists, there will be a summary of sections at the end to discuss)
- If user or the task being run provides a checklist name:
-
Document and Artifact Gathering
- Each checklist will specify its required documents/artifacts at the beginning
- Follow the checklist's specific instructions for what to gather, generally a file can be resolved in the docs folder, if not or unsure, halt and ask or confirm with the user.
-
Checklist Processing
If in interactive mode:
- Work through each section of the checklist one at a time
- For each section:
- Review all items in the section following instructions for that section embedded in the checklist
- Check each item against the relevant documentation or artifacts as appropriate
- Present summary of findings for that section, highlighting warnings, errors and non applicable items (rationale for non-applicability).
- Get user confirmation before proceeding to next section or if any thing major do we need to halt and take corrective action
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.
- 9d ago First seen · 93 lines · 0 tokens per session scan A 69f7fc2cf146
execute-checklist is a command published in the GitHub repository julianobarbosa/azure-finops-mcp-server (2 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 834 tokens. A static security scan graded it A with 0 findings. It is 94% identical to execute-checklist, differing in 2 lines, and is treated as a copy.
Other commands, from other repositories
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.