Borrowing it
Nothing to install: this file belongs to e0ipso/drupal-bridge-mcp. 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/e0ipso/drupal-bridge-mcp/main/.claude/commands/tasks/create-plan.mdgit clone --depth 1 https://github.com/e0ipso/drupal-bridge-mcpWrote 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/e0ipso/drupal-bridge-mcp/create-plan)<a href="https://agentmods.dev/commands/e0ipso/drupal-bridge-mcp/create-plan"><img src="https://agentmods.dev/badge/commands/e0ipso/drupal-bridge-mcp/create-plan/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/e0ipso/drupal-bridge-mcp/create-plan"><img src="https://agentmods.dev/badge/commands/e0ipso/drupal-bridge-mcp/create-plan.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 | $0.00012 | $0.01149 |
| Opus 5.5 | $0.00005 | $0.00460 |
| Sonnet 5.5 | $0.00002 | $0.00230 |
| Haiku 4.5 | $0.00001 | $0.00115 |
Grade A, and why
create-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comprehensive Plan Creation
Assistant Configuration
Before proceeding with this command, you MUST load and respect the assistant's configuration:
Run the following scripts:
ASSISTANT=$(node .ai/task-manager/config/scripts/detect-assistant.cjs)
node .ai/task-manager/config/scripts/read-assistant-config.cjs "$ASSISTANT"
The output above contains your global and project-level configuration rules. You MUST keep these rules and guidelines in mind during all subsequent operations in this command.
Think harder and use tools.
You are a comprehensive task planning assistant. Your role is to think hard to create detailed, actionable plans based on user input while ensuring you have all necessary context before proceeding.
Include .ai/task-manager/config/TASK_MANAGER.md for the directory structure of tasks.
Instructions
The user input is:
If no user input is provided stop immediately and show an error message to the user.
Process
Use your internal Todo task tool to track the plan generation:
- Read and execute .ai/task-manager/config/hooks/PRE_PLAN.md
- User input and context analysis
- Clarification questions
- Plan generation: Executive Summary
- Plan generation: Detailed Steps
- Plan generation: Risk Considerations
- Plan generation: Success Metrics
- Read and execute .ai/task-manager/config/hooks/POST_PLAN.md
Step 1: Context Analysis
Before creating any plan, analyze the user's request for:
- Objective: What is the end goal?
- Scope: What are the boundaries and constraints?
- Resources: What tools, budget, or team are available?
- Success Criteria: How will success be measured?
- Dependencies: What prerequisites or blockers exist?
- Technical Requirements: What technologies or skills are needed?
Step 2: Clarification Phase
If any critical context is missing:
- Identify specific gaps in the information provided
- Ask targeted follow-up questions grouped by category
- Wait for user responses before proceeding to planning
- Frame questions clearly with examples when helpful
- Be extra cautious. Users miss important context very often. Don't hesitate to ask for clarifications.
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 · 156 lines · 12 tokens per session scan A 86d5bf26d75d
create-plan is a command published in the GitHub repository e0ipso/drupal-bridge-mcp (5 stars, last pushed 11mo ago), licensed MIT. It adds 12 tokens to every session and 1,149 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-31.
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.
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.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.
speckit.bug.test
Validate that a previously fixed bug is resolved and record the verification report.