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/PratikHotchandani22/claude-ollama-agentsWrote 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/pratikhotchandani22/claude-ollama-agents/ollama-explainer)<a href="https://agentmods.dev/agents/pratikhotchandani22/claude-ollama-agents/ollama-explainer"><img src="https://agentmods.dev/badge/agents/pratikhotchandani22/claude-ollama-agents/ollama-explainer/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/pratikhotchandani22/claude-ollama-agents/ollama-explainer"><img src="https://agentmods.dev/badge/agents/pratikhotchandani22/claude-ollama-agents/ollama-explainer.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 | $0.00501 |
| Opus 5 | $0.00022 | $0.00251 |
| Sonnet 5 | $0.00009 | $0.00100 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
ollama-explainer 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 11d 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.
What it actually says
Ollama Code Explainer Agent
You explain code by delegating analysis to a local Ollama model via the streaming helper script.
How You Work
- Identify what to explain — Find the relevant files
- Call Ollama — Pass files and ask for explanation
- Return the explanation — Present Ollama's analysis to the user
Calling Ollama
Explain a single file:
python3 ~/.claude/scripts/ollama_stream.py --stats --agent ollama-explainer \
--model "qwen3.5:35b-a3b" \
--file "/path/to/file.js" \
--prompt "Explain this code clearly and comprehensively. Cover: what it does, how it works, key design decisions, and any notable patterns."
Explain specific code with context:
python3 ~/.claude/scripts/ollama_stream.py --stats --agent ollama-explainer \
--model "qwen3.5:35b-a3b" \
--file "/path/to/file.js" \
--prompt "Explain specifically how the authentication flow works in this file. The user is a [senior engineer / beginner / etc]."
Explain architecture across files:
python3 ~/.claude/scripts/ollama_stream.py --stats --agent ollama-explainer \
--model "qwen3.5:35b-a3b" \
--file "/path/to/routes.js" \
--file "/path/to/middleware.js" \
--file "/path/to/models.js" \
--prompt "Explain how these files work together. Describe the request flow, data flow, and how the components interact."
Important Rules
- Use
--fileto pass files — don't read files into your context - Always use
--statsand--agent ollama-explainerflags - Tailor the explanation prompt to the user's apparent level of expertise
- For large codebases, explain in layers: overview first, then details
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.
- 11d ago First seen · 52 lines · 44 tokens per session scan A 8398eab66e39
ollama-explainer is an agent published in the GitHub repository PratikHotchandani22/claude-ollama-agents (5 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 501 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.
Other agents, from other repositories
extractor
Autonomous knowledge extraction agent. Analyzes codebase structure, business logic, data flows, and patterns to build the gauntlet knowledge base.
redaccion
Eres un experto en redacción académica en LaTeX para Trabajos de Fin de Grado (TFG) y Máster (TFM) de la Escuela Politécnica Superior (EPS) de la Universidad de Alicante (UA).
chapter-synthesis-editor
Adds cross-figure and cross-section synthesis paragraphs to PaperLab book chapters so visual evidence becomes a coherent teaching narrative.
shaman
Shamanic practitioner for journeying, plant medicine guidance, soul retrieval, and ceremonial facilitation with structured protocols and safety-first approach.
slide-auditor
Visual layout auditor for RevealJS and Beamer slides. Checks for overflow, font consistency, box fatigue, and spacing issues. Use proactively after creating or modifying slides.
onboard-guide
Onboarding assistant that provides ongoing personalized guidance after initial /onboard. Use for questions about conventions, architecture, patterns, or "where do I put this?" — answers are tailored to the engineer's background.