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 skills add lofcz/LLMTornado --skill codebase-context-extractorgit clone --depth 1 https://github.com/lofcz/LLMTornadoWrote 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/skills/lofcz/llmtornado/codebase-context-extractor)<a href="https://agentmods.dev/skills/lofcz/llmtornado/codebase-context-extractor"><img src="https://agentmods.dev/badge/skills/lofcz/llmtornado/codebase-context-extractor/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/skills/lofcz/llmtornado/codebase-context-extractor"><img src="https://agentmods.dev/badge/skills/lofcz/llmtornado/codebase-context-extractor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Data Exfiltration · line 12 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 | $0.00042 | $0.01280 |
| Opus 5.5 | $0.00017 | $0.00512 |
| Sonnet 5.5 | $0.00008 | $0.00256 |
| Haiku 4.5 | $0.00004 | $0.00128 |
Grade A, and why
codebase-context-extractor 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 1mo 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Context Extractor Skill
Overview
This skill provides a comprehensive context extraction system for large codebases. It intelligently analyzes code structure, dependencies, and relationships to extract relevant context for understanding, debugging, or modifying code.
Trigger Words
- "extract context"
- "codebase context"
- "code context"
- "analyze codebase"
- "codebase analysis"
- "code structure"
- "dependency analysis"
- "code relationships"
- "understand codebase"
- "map codebase"
When to Use This Skill
Use this skill when you need to:
- Understand the structure and organization of a large codebase
- Extract relevant context for a specific function, class, or module
- Analyze dependencies and relationships between code components
- Generate documentation or summaries of code sections
- Prepare context for code modifications or debugging
- Identify entry points and execution flows
- Map out API surfaces and public interfaces
- Understand data flow and state management
Instructions
When this skill is triggered, execute the context_extractor.py script with appropriate parameters.
Basic Usage
python /projects/workspace/codebase-context-extractor/context_extractor.py \
--target-path <path_to_codebase> \
--mode <extraction_mode> \
--output <output_file>
Extraction Modes
- full - Complete codebase analysis with all components
- targeted - Focus on specific files, functions, or classes
- dependency - Map dependencies and imports
- flow - Trace execution flows and call chains
- api - Extract public interfaces and API surfaces
- data - Analyze data structures and models
- hierarchy - Show class hierarchies and inheritance
- summary - Generate high-level overview
Parameters
--target-path(required): Path to the codebase to analyze--mode(required): Extraction mode (see above)--output(optional): Output file path (default: stdout)--focus(optional): Specific file, class, or function to focus on--depth(optional): Maximum depth for traversal (default: unlimited)--include-tests(optional): Include test files in analysis (default: false)--language(optional): Programming language (auto-detected if not specified)--format(optional): Output format (markdown, json, yaml, text) (default: markdown)--exclude(optional): Patterns to exclude (comma-separated)
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 171 lines · 42 tokens per session scan A 08efb4843229
codebase-context-extractor is a skill published in the GitHub repository lofcz/LLMTornado (645 stars, last pushed 6d ago), licensed MIT. It adds 42 tokens to every session and 1,280 once invoked, about $0.0002 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 2026-08-30.
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