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/mort-lab/excel-mcp/ts-create-base-prpgit clone --depth 1 https://github.com/mort-lab/excel-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/mort-lab/excel-mcp/ts-create-base-prp)<a href="https://agentmods.dev/commands/mort-lab/excel-mcp/ts-create-base-prp"><img src="https://agentmods.dev/badge/commands/mort-lab/excel-mcp/ts-create-base-prp.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 | $0.00000 | $0.00866 |
| Opus 5 | $0.00000 | $0.00433 |
| Sonnet 5 | $0.00000 | $0.00173 |
| Haiku 4.5 | $0.00000 | $0.00087 |
Grade A, and why
TS-create-base-prp 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.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create BASE PRP
Feature: $ARGUMENTS
Generate a complete PRP for TypeScript/JavaScript feature implementation with deep and thorough research. Ensure rich context is passed to the AI through the PRP to enable one pass implementation success through self-validation and iterative refinement.
The AI agent only gets the context you are appending to the PRP and its own training data. Assume the AI agent has access to the codebase and the same knowledge cutoff as you, so its important that your research findings are included or referenced in the PRP. The Agent has Websearch capabilities, so pass urls to documentation and examples.
Research Process
During the research process, create clear tasks and spawn as many agents and subagents as needed using the batch tools. The deeper research we do here the better the PRP will be. we optimize for chance of success and not for speed.
-
Codebase Analysis in depth
- Create clear todos and spawn subagents to search the codebase for similar features/patterns Think hard and plan your approach
- Identify all the necessary files to reference in the PRP
- Note all existing conventions to follow (TypeScript patterns, React patterns, etc.)
- Check existing test patterns for validation approach (Jest, Vitest, Cypress, etc.)
- Use the batch tools to spawn subagents to search the codebase for similar features/patterns
-
External Research at scale
- Create clear todos and spawn with instructions subagents to do deep research for similar features/patterns online and include urls to documentation and examples
- Library documentation (include specific URLs for TypeScript/JavaScript libraries)
- For critical pieces of documentation add a .md file to PRPs/ai_docs and reference it in the PRP with clear reasoning and instructions
- Implementation examples (GitHub/StackOverflow/blogs with TypeScript focus)
- Best practices and common pitfalls found during research
- Use the batch tools to spawn subagents to search for similar features/patterns online and include urls to documentation and examples
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 · 91 lines · 0 tokens per session scan A 299feebb80d0
TS-create-base-prp is a command published in the GitHub repository mort-lab/excel-mcp (5 stars, last pushed 28d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 866 tokens. 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
review-epo-claims
Analyze patent claims for EPO Art. 84 EPC compliance - clarity, conciseness, support by description.
instructions
Use the instructions command to print the CLI playbook and current server inventory for AI agents using a running 1MCP serve instance.
ingest-dev
Ingest a URL, directory, or file into your knowledge base. remember = a specific durable fact, ingest = a URL, learn = a distilled lesson that gets retrieval preference.
quarry
Manage your quarry knowledge base.
remember-dev
Remember inline text content in your knowledge base. remember = a specific durable fact, ingest = a URL, learn = a distilled lesson that gets retrieval preference.
scout
Scout vetted GitHub candidates for a thin shelf (or a stale entry's successor), deduped against the library, ending in /add-entry offers.