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/cakemail/cakemail-api-documentation-mcp/create-deep-research-promptgit clone --depth 1 https://github.com/cakemail/cakemail-api-documentation-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/cakemail/cakemail-api-documentation-mcp/create-deep-research-prompt)<a href="https://agentmods.dev/commands/cakemail/cakemail-api-documentation-mcp/create-deep-research-prompt"><img src="https://agentmods.dev/badge/commands/cakemail/cakemail-api-documentation-mcp/create-deep-research-prompt.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 5.1 | $0.00000 | $0.01435 |
| Opus 5 | $0.00000 | $0.00718 |
| Sonnet 5 | $0.00000 | $0.00287 |
| Haiku 4.5 | $0.00000 | $0.00144 |
Grade A, and why
create-deep-research-prompt 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 5d 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
98% identical to create-deep-research-prompt — 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/create-deep-research-prompt Task
When this command is used, execute the following task:
Create Deep Research Prompt Task
This task helps create comprehensive research prompts for various types of deep analysis. It can process inputs from brainstorming sessions, project briefs, market research, or specific research questions to generate targeted prompts for deeper investigation.
Purpose
Generate well-structured research prompts that:
- Define clear research objectives and scope
- Specify appropriate research methodologies
- Outline expected deliverables and formats
- Guide systematic investigation of complex topics
- Ensure actionable insights are captured
Research Type Selection
CRITICAL: First, help the user select the most appropriate research focus based on their needs and any input documents they've provided.
1. Research Focus Options
Present these numbered options to the user:
-
Product Validation Research
- Validate product hypotheses and market fit
- Test assumptions about user needs and solutions
- Assess technical and business feasibility
- Identify risks and mitigation strategies
-
Market Opportunity Research
- Analyze market size and growth potential
- Identify market segments and dynamics
- Assess market entry strategies
- Evaluate timing and market readiness
-
User & Customer Research
- Deep dive into user personas and behaviors
- Understand jobs-to-be-done and pain points
- Map customer journeys and touchpoints
- Analyze willingness to pay and value perception
-
Competitive Intelligence Research
- Detailed competitor analysis and positioning
- Feature and capability comparisons
- Business model and strategy analysis
- Identify competitive advantages and gaps
-
Technology & Innovation Research
- Assess technology trends and possibilities
- Evaluate technical approaches and architectures
- Identify emerging technologies and disruptions
- Analyze build vs. buy vs. partner options
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.
- 5d ago First seen · 285 lines · 0 tokens per session scan A b64a0300822a
create-deep-research-prompt is a command published in the GitHub repository cakemail/cakemail-api-documentation-mcp (0 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,435 tokens. A static security scan graded it A with 0 findings. It is 98% identical to create-deep-research-prompt, 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.