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 skills/huzaifa525/claude-code-optimizer/gen-contextnpx skills add huzaifa525/claude-code-optimizer --skill gen-contextgit clone --depth 1 https://github.com/huzaifa525/claude-code-optimizerWrote 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/huzaifa525/claude-code-optimizer/gen-context)<a href="https://agentmods.dev/skills/huzaifa525/claude-code-optimizer/gen-context"><img src="https://agentmods.dev/badge/skills/huzaifa525/claude-code-optimizer/gen-context.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.00324 |
| Opus 5 | $0.00012 | $0.00162 |
| Sonnet 5 | $0.00005 | $0.00065 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
gen-context 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 3d 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
Generate a comprehensive but concise project context by analyzing the codebase.
Steps
- Read package.json / pyproject.toml / Cargo.toml → identify stack, dependencies, scripts
- Scan top-level structure →
Glob("*")thenGlob("src/*")or equivalent - Find entry points → main files, index files, app setup files
- Identify framework → Express, Next.js, FastAPI, Django, etc.
- Check for existing CLAUDE.md → read current instructions
- Read recent git history →
git log --oneline -10 - Identify key patterns → how routes/components/models are structured
Return Format
## Project: [name]
## Stack: [framework, language, database, etc.]
### Commands
- Build: [command]
- Test: [command]
- Dev: [command]
### Entry Points
- [file] → [what it wires together]
### Structure
- [dir/] → [purpose]
### Recent Activity
- [last 5 commits summarized]
### Suggested CLAUDE.md Updates
- [anything missing from current CLAUDE.md]
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.
- 3d ago First seen · 46 lines · 24 tokens per session scan A 07c85cd85fe5
gen-context is a skill published in the GitHub repository huzaifa525/claude-code-optimizer (9 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 324 once invoked, about $0.0001 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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