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.
git clone --depth 1 https://github.com/hfredrick69/deep-research-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/rules/hfredrick69/deep-research-mcp-server/02-chunking-and-splitting-rules)<a href="https://agentmods.dev/rules/hfredrick69/deep-research-mcp-server/02-chunking-and-splitting-rules"><img src="https://agentmods.dev/badge/rules/hfredrick69/deep-research-mcp-server/02-chunking-and-splitting-rules/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/rules/hfredrick69/deep-research-mcp-server/02-chunking-and-splitting-rules"><img src="https://agentmods.dev/badge/rules/hfredrick69/deep-research-mcp-server/02-chunking-and-splitting-rules.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 | $0.00029 | $0.00275 |
| Opus 5.5 | $0.00012 | $0.00110 |
| Sonnet 5.5 | $0.00006 | $0.00055 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
02-chunking-and-splitting-rules 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 yesterday.
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.
What it actually says
Chunking and Text Splitting Rules
Last reviewed: 2025-08-11
Use chunking that preserves coherence while fitting model/token budgets.
Defaults
- Recursive splitter with ordered separators (e.g.,
\n\n,\n, - Semantic splitter only when embeddings are available and budgeted; otherwise stick to recursive.
- Chunk size/overlap: Tune per task; start with conservative sizes, validate with recall/precision in retrieval.
Project Guidance
- Use
createResearchSplitter()insrc/ai/text-splitter.ts. - Avoid external calls in tests; mock
generateTextEmbedding()when exercising semantic splitting. - Ensure each chunk carries sufficient context for summarization prompts; consider chunk expansion around headings.
Anti-Patterns
- Overlapping too much (wastes tokens) or too little (context loss at boundaries).
- Large chunks that exceed downstream prompt budgets when batched.
References
- Chunking strategies (Pinecone): (https://www.pinecone.io/learn/chunking-strategies/)
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.
- yesterday First seen · 28 lines · 29 tokens per session scan A 8616d43f0550
02-chunking-and-splitting-rules is a cursor rule published in the GitHub repository hfredrick69/deep-research-mcp-server (0 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 275 once invoked, about $0.0001 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 2026-10-30.
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