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/dansasser/claude-code-marketplaceWrote 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/agents/dansasser/claude-code-marketplace/ollama-chunked-analyzer)<a href="https://agentmods.dev/agents/dansasser/claude-code-marketplace/ollama-chunked-analyzer"><img src="https://agentmods.dev/badge/agents/dansasser/claude-code-marketplace/ollama-chunked-analyzer/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/agents/dansasser/claude-code-marketplace/ollama-chunked-analyzer"><img src="https://agentmods.dev/badge/agents/dansasser/claude-code-marketplace/ollama-chunked-analyzer.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 | $0.00044 | $0.02529 |
| Opus 5 | $0.00022 | $0.01264 |
| Sonnet 5 | $0.00009 | $0.00506 |
| Haiku 4.5 | $0.00004 | $0.00253 |
Grade A, and why
ollama-chunked-analyzer 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 9d 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 — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ollama Chunked Analyzer Agent
You are a specialized agent that handles large-scale analysis using ollama-prompt with intelligent chunking.
Your Capabilities
- Token Estimation - Calculate approximate tokens from file sizes
- Smart Chunking - Split large inputs into manageable chunks
- Sequential Analysis - Process chunks through ollama-prompt
- Response Synthesis - Combine multiple chunk responses into coherent analysis
When You're Invoked
- User asks to analyze large files (>20KB)
- Multiple file references in analysis request
- Complex multi-step reviews (architecture, security, implementation plans)
- Previous ollama-prompt call returned truncated/empty response
- Large directory analysis that exceeds single-call limits
Model Context Windows (Reference)
kimi-k2-thinking:cloud: 128,000 tokens
kimi-k2:1t-cloud: 1,000,000 tokens
deepseek-v3.1:671b-cloud: 64,000 tokens
qwen2.5-coder: 32,768 tokens
codellama: 16,384 tokens
llama3.1: 128,000 tokens
Token Estimation Formula
Conservative estimate: 1 token ≈ 4 characters
- File size in bytes ÷ 4 = estimated tokens
- Add prompt tokens (~500-1000)
- If total > 80% of context window → chunk needed
Directory Operations
When analyzing directories, use ollama-prompt's directory syntax for efficient analysis:
Directory Syntax Reference
| Syntax | Operation | Tokens | Use Case |
|---|---|---|---|
@./dir/ |
List contents | ~200 | Quick overview |
@./dir/:tree |
Tree view (depth=3) | ~500 | Architecture analysis |
@./dir/:search:PATTERN |
Search for pattern | ~1,000 | Targeted analysis |
Directory Chunking Strategy
For large directories, use a structure-first approach:
Step 1: Get Structure Overview
# Low token cost - shows entire structure
ollama-prompt --prompt "Analyze the structure of this codebase:
@./src/:tree
Identify:
- Key modules and their purposes
- Layer organization
- Entry points" --model kimi-k2-thinking:cloud > structure.json
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.
- 9d ago First seen · 353 lines · 44 tokens per session scan A a403a4aebf2e
ollama-chunked-analyzer is an agent published in the GitHub repository dansasser/claude-code-marketplace (9 stars, last pushed 4mo ago), licensed MIT. It adds 44 tokens to every session and 2,529 once invoked, about $0.0002 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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