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 FradSer/dotclaude --skill code-contextgit clone --depth 1 https://github.com/FradSer/dotclaudeWrote 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/fradser/dotclaude/code-context)<a href="https://agentmods.dev/skills/fradser/dotclaude/code-context"><img src="https://agentmods.dev/badge/skills/fradser/dotclaude/code-context/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/fradser/dotclaude/code-context"><img src="https://agentmods.dev/badge/skills/fradser/dotclaude/code-context.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 | $0.00093 | $0.02208 |
| Opus 5.5 | $0.00037 | $0.00883 |
| Sonnet 5.5 | $0.00019 | $0.00442 |
| Haiku 4.5 | $0.00009 | $0.00221 |
Grade C, and why
code-context scanned grade C with 1 finding 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **Git clone**: Agent clones to `/tmp/`, reads entry points and core modules, runs `rm -rf` cleanup, returns file structure summary and key patterns. How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Context Retrieval
This skill provides 5 methods for retrieving code context. Select methods based on the target: public GitHub repos, library docs, code search, direct inspection, or post-clone web enrichment.
Token Isolation (Critical)
Never run any external lookup in the main context. Always spawn Task agents:
- DeepWiki: Agent calls
read_wiki_structure/read_wiki_contents/ask_question, extracts architecture summary and key relationships, returns concise overview. - Context7: Agent calls
resolve-library-idthenquery-docs, extracts the minimum viable API surface and usage examples, returns copyable snippets with version notes. - Exa: Agent calls
get_code_context_exa, extracts minimum viable snippets, deduplicates near-identical results (mirrors, forks, repeated StackOverflow answers), returns copyable snippets + brief explanation. - Git clone: Agent clones to
/tmp/, reads entry points and core modules, runsrm -rfcleanup, returns file structure summary and key patterns. - Web Search+Fetch: Agent runs
WebSearchwith version-anchored queries derived from clone findings, callsWebFetchon high-signal URLs, returns only validated insights cross-referenced against cloned code.
Main context stays clean regardless of search volume. Only final summaries return to the caller.
Method 1: DeepWiki (AI-powered repo documentation)
Best for: Well-known public GitHub repositories where you need architecture overview, component explanations, or high-level understanding fast.
Tools: read_wiki_structure, read_wiki_contents, ask_question
Process:
- Call
read_wiki_structurewith the owner/repo (e.g.,"facebook/react") to get topic list - Call
read_wiki_contentsfor relevant topics, orask_questionfor targeted queries - Use when you need: architecture diagrams, component relationships, design decisions
Strengths: Zero setup, instant AI-summarized documentation, good for onboarding to unfamiliar repos.
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 · 156 lines · 93 tokens per session scan C d04902f60eac
code-context is a skill published in the GitHub repository FradSer/dotclaude (593 stars, last pushed 7d ago), licensed MIT. It adds 93 tokens to every session and 2,208 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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