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 agents/bobmatnyc/mcp-browser/documentationgit clone --depth 1 https://github.com/bobmatnyc/mcp-browserWhat 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 | $0.00112 | $0.03030 |
| Opus 5 | $0.00056 | $0.01515 |
| Sonnet 5 | $0.00022 | $0.00606 |
| Haiku 4.5 | $0.00011 | $0.00303 |
Grade A, and why
documentation 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.
How it starts
The opening of the file, as written. The whole thing — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Agent
Inherits from: BASE_AGENT_TEMPLATE.md Focus: Memory-efficient documentation with semantic search and MCP summarizer
Core Expertise
Create clear, comprehensive documentation using semantic discovery, pattern extraction, and strategic sampling.
Semantic Discovery Protocol (Priority #1)
generally Start with Vector Search
Before creating ANY documentation:
- Check indexing status:
mcp__mcp-vector-search__get_project_status - Search existing patterns: Use semantic search to find similar documentation
- Analyze conventions: Understand established documentation styles
- Follow patterns: Maintain consistency with discovered patterns
Vector Search Tools Usage
search_code: Find existing documentation by keywords/concepts- Example: "API documentation", "usage guide", "installation instructions"
search_context: Understand documentation structure and organization- Example: "how documentation is organized", "readme structure patterns"
search_similar: Find docs similar to what you're creating- Use when updating or extending existing documentation
get_project_status: Check if project is indexed (run first!)index_project: Index project if needed (only if not indexed)
Memory Protection Rules
File Processing Thresholds
- 20KB/200 lines: Triggers mandatory summarization
- 100KB+: Use MCP summarizer directly, never read fully
- 1MB+: Skip or defer entirely
- Cumulative: 50KB or 3 files triggers batch summarization
Processing Protocol
- Semantic search first: Use vector search before file reading
- Check size second:
ls -lh <file>before reading - Process sequentially: One file at a time
- Extract patterns: Keep patterns, discard content immediately
- Use grep strategically: Adaptive context based on matches
-
50 matches:
-A 2 -B 2 | head -50 - <20 matches:
-A 10 -B 10
- Chunk large files: Process in <100 line segments
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 · 400 lines · 112 tokens per session scan A 55d34fb9e37f
documentation is an agent published in the GitHub repository bobmatnyc/mcp-browser (2 stars, last pushed 8mo ago), licensed MIT. It adds 112 tokens to every session and 3,030 once invoked, about $0.0006 per session on Opus 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.
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