Best-in-class embeddings, rerankers, web reader, deepsearch, small language models. Search AI for multilingual and multimodal data.
Based on the limited social mentions provided, there's insufficient substantive user feedback to draw meaningful conclusions about Jina AI's strengths, complaints, or pricing sentiment. The social mentions consist mainly of repetitive YouTube titles and one Reddit post that mentions Claude Code rather than Jina AI directly. Without actual user reviews or detailed discussions about Jina AI's performance, features, or value proposition, I cannot provide a reliable summary of user sentiment toward this tool.
Mentions (30d)
0
Reviews
0
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2
GitHub Stars
21,857
2,239 forks
Based on the limited social mentions provided, there's insufficient substantive user feedback to draw meaningful conclusions about Jina AI's strengths, complaints, or pricing sentiment. The social mentions consist mainly of repetitive YouTube titles and one Reddit post that mentions Claude Code rather than Jina AI directly. Without actual user reviews or detailed discussions about Jina AI's performance, features, or value proposition, I cannot provide a reliable summary of user sentiment toward this tool.
Features
Industry
information technology & services
Employees
45
Funding Stage
Merger / Acquisition
Total Funding
$32.0M
3,991
GitHub followers
264
GitHub repos
21,857
GitHub stars
20
npm packages
28
HuggingFace models
I built an all-in-one dev environment for Claude Code -- 11 agents, 36 commands, 15 skills in 5 minutes
If you've spent any real time with Claude Code, you've probably hit the same wall I did: it's incredibly powerful out of the box, but getting it to work *consistently well* across projects takes a lot of manual setup. Custom agents, security hooks, slash commands, workflow rules -- you end up rebuilding the same infrastructure every time you start something new. After months of iterating on my own Claude Code setup across dozens of client projects (I run a small AI automation consultancy), I decided to package everything into an open-source framework. I'm calling it **Claude Forge**, and the easiest way to describe it is: **oh-my-zsh for Claude Code**. Just like oh-my-zsh transforms a basic terminal into a fully-featured shell environment, Claude Forge transforms Claude Code from a capable CLI into a complete development environment -- with agents, commands, skills, hooks, and rules all pre-wired and ready to go. ## The Problem Every time I started a new project with Claude Code, I found myself: 1. **Re-creating the same agents** -- planner, code reviewer, security reviewer, TDD guide... I'd copy-paste agent definitions from project to project 2. **Writing the same hook scripts** -- secret filtering, destructive SQL guards, remote command protection 3. **Defining the same workflow rules** -- coding style, git conventions, security checklists 4. **Missing security gaps** -- forgetting to add a hook here, a rule there, until something slipped through The real pain wasn't any single piece -- it was that there was no unified way to manage all of these together. I had agents in one folder, hooks scattered around, rules in various formats, and no way to share improvements across projects. ## What Claude Forge Does One `git clone` + `./install.sh` and you get: | Component | Count | What it does | |-----------|-------|-------------| | **Agents** | 11 | Specialized AI agents (planner, architect, code-reviewer, security-reviewer, TDD guide, database reviewer, + 5 more) | | **Commands** | 36 | Slash commands like `/plan`, `/tdd`, `/code-review`, `/handoff-verify`, `/commit-push-pr`, `/auto` | | **Skills** | 15 | Multi-step workflows (build system detection, security pipeline, eval harness, team orchestrator) | | **Hooks** | 14 | Automation hooks including 6-layer security (secret filtering, SQL injection guard, remote command protection) | | **Rules** | 8 | Coding style, security, git workflow, golden principles | | **MCP Servers** | 6 | context7, memory, exa, github, fetch, jina-reader | ## How It Works The architecture is dead simple -- it's all **symlinks**. ```bash git clone --recurse-submodules https://github.com/sangrokjung/claude-forge.git cd claude-forge ./install.sh ``` The installer creates symlinks from the repo to `~/.claude/`. That means: - **`git pull` updates everything instantly** -- no reinstall needed - **Your personal config stays separate** -- use `settings.local.json` for overrides - **Easy to fork and customize** -- it's just markdown files and shell scripts ## The Workflows Are What Make It Click The individual components are useful, but the real value is how they chain together into workflows: **Feature Development:** ``` /plan --> /tdd --> /code-review --> /handoff-verify --> /commit-push-pr ``` **Bug Fix (fast path):** ``` /explore --> /tdd --> /verify-loop --> /quick-commit ``` **Security Audit:** ``` /security-review --> /stride-analysis-patterns --> /security-compliance ``` **Full Autopilot:** ``` /auto login page ``` (Yes, one command that goes from planning to PR.) ## The Security Layer This is the part I'm most proud of. Claude Forge includes a **6-layer security defense**: 1. **Secret filtering** -- catches leaked API keys, tokens, passwords in output 2. **Remote command guard** -- blocks unsafe patterns like `curl | bash` 3. **DB protection** -- prevents destructive SQL (DROP, TRUNCATE, DELETE without WHERE) 4. **Security auto-trigger** -- scans code changes for vulnerabilities as you write 5. **Rate limiting** -- prevents MCP server abuse 6. **MCP usage tracking** -- monitors external tool usage These run automatically as hooks. You don't have to think about them -- they just work. ## The Agent System 11 specialized agents, split by capability: **Opus agents (6)** for deep analysis: - `planner` -- implementation planning for complex features - `architect` -- system design and scalability decisions - `code-reviewer` -- quality, security, maintainability - `security-reviewer` -- OWASP Top 10, secrets, injection detection - `tdd-guide` -- test-driven development enforcement - `database-reviewer` -- PostgreSQL/Supabase optimization **Sonnet agents (5)** for fast execution: - `build-error-resolver` -- fix build errors with minimal diffs - `e2e-runner` -- Playwright E2E test generation - `refactor-cleaner` -- dead code cleanup - `doc-updater` -- documentation updates - `verify-agent` -- fresh-context verification Each agent has its ow
View originalhow to save 80% on your claude bill with better context
been building web apps with claude lately and those token limits have honestly started hitting me too. i'm using claude 4.6 sonnet for a research tool, but feeding it raw web data was absolutely nuking my limits. i'm putting together the stuff that actually worked for me to save tokens and keep the bill down: switch to markdown first. stop sending raw html. use tools like firecrawl to strip out the nested divs and script junk so you only pay for the actual text. don't let your prompt cache go cold. anthropic's prompt caching is a huge relief, but it only works if your data is consistent. watch out for the 200k token "premium" jump. anthropic now charges nearly double for inputs over 200k tokens on the new opus/sonnet 4.6 models. keep your context under that limit to avoid the surcharge strip the nav and footer. the website's "about us" and "careers" links in the footer are just burning your money every time you hit send. use jina reader for quick hits. for simple single-page reads, jina is a great way to get a clean text version without the crawler bloat. truncate your context. if a documentation page is 20k words, just take the first 5k. most of the "meat" is usually at the top anyway. clean your data with unstructured.io. if you are dealing with messy pdfs alongside web data, this helps turn the chaos into a clean schema claude actually understands. map before you crawl. don't scrape every subpage blindly. i use the map feature in firecrawl to find the specific documentation urls that actually matter for your prompt, if you use another tool, prefer doing this. use haiku for the "trash" work. use claude 4.5 haiku to summarize or filter data before feeding it into the expensive models like opus. use smart chunking. use llama-index to break your data into semantic chunks so you only retrieve the exact paragraph the ai needs for that specific prompt. cap your "extended thinking" depth. for opus 4.6, set thinking: {type: "adaptive"} with effort: "low" or "medium". the old budget_tokens param is deprecated on 4.6. thinking tokens are billed at the output rate, so if you leave effort on high, claude thinks hard on every single reply including the simple ones and your bill will hurt. set hard usage limits. set your spending tiers in the anthropic console so a buggy loop doesn't drain your bank account while you're asleep. feel free to roast my setup or add better tips if you have thembeen building web apps with claude lately and those token limits have honestly started hitting me too. i'm using claude 4.6 sonnet for a research tool, but feeding it raw web data was absolutely nuking my limits. submitted by /u/Grouchy_Subject_2777 [link] [comments]
View originalI built an all-in-one dev environment for Claude Code -- 11 agents, 36 commands, 15 skills in 5 minutes
If you've spent any real time with Claude Code, you've probably hit the same wall I did: it's incredibly powerful out of the box, but getting it to work *consistently well* across projects takes a lot of manual setup. Custom agents, security hooks, slash commands, workflow rules -- you end up rebuilding the same infrastructure every time you start something new. After months of iterating on my own Claude Code setup across dozens of client projects (I run a small AI automation consultancy), I decided to package everything into an open-source framework. I'm calling it **Claude Forge**, and the easiest way to describe it is: **oh-my-zsh for Claude Code**. Just like oh-my-zsh transforms a basic terminal into a fully-featured shell environment, Claude Forge transforms Claude Code from a capable CLI into a complete development environment -- with agents, commands, skills, hooks, and rules all pre-wired and ready to go. ## The Problem Every time I started a new project with Claude Code, I found myself: 1. **Re-creating the same agents** -- planner, code reviewer, security reviewer, TDD guide... I'd copy-paste agent definitions from project to project 2. **Writing the same hook scripts** -- secret filtering, destructive SQL guards, remote command protection 3. **Defining the same workflow rules** -- coding style, git conventions, security checklists 4. **Missing security gaps** -- forgetting to add a hook here, a rule there, until something slipped through The real pain wasn't any single piece -- it was that there was no unified way to manage all of these together. I had agents in one folder, hooks scattered around, rules in various formats, and no way to share improvements across projects. ## What Claude Forge Does One `git clone` + `./install.sh` and you get: | Component | Count | What it does | |-----------|-------|-------------| | **Agents** | 11 | Specialized AI agents (planner, architect, code-reviewer, security-reviewer, TDD guide, database reviewer, + 5 more) | | **Commands** | 36 | Slash commands like `/plan`, `/tdd`, `/code-review`, `/handoff-verify`, `/commit-push-pr`, `/auto` | | **Skills** | 15 | Multi-step workflows (build system detection, security pipeline, eval harness, team orchestrator) | | **Hooks** | 14 | Automation hooks including 6-layer security (secret filtering, SQL injection guard, remote command protection) | | **Rules** | 8 | Coding style, security, git workflow, golden principles | | **MCP Servers** | 6 | context7, memory, exa, github, fetch, jina-reader | ## How It Works The architecture is dead simple -- it's all **symlinks**. ```bash git clone --recurse-submodules https://github.com/sangrokjung/claude-forge.git cd claude-forge ./install.sh ``` The installer creates symlinks from the repo to `~/.claude/`. That means: - **`git pull` updates everything instantly** -- no reinstall needed - **Your personal config stays separate** -- use `settings.local.json` for overrides - **Easy to fork and customize** -- it's just markdown files and shell scripts ## The Workflows Are What Make It Click The individual components are useful, but the real value is how they chain together into workflows: **Feature Development:** ``` /plan --> /tdd --> /code-review --> /handoff-verify --> /commit-push-pr ``` **Bug Fix (fast path):** ``` /explore --> /tdd --> /verify-loop --> /quick-commit ``` **Security Audit:** ``` /security-review --> /stride-analysis-patterns --> /security-compliance ``` **Full Autopilot:** ``` /auto login page ``` (Yes, one command that goes from planning to PR.) ## The Security Layer This is the part I'm most proud of. Claude Forge includes a **6-layer security defense**: 1. **Secret filtering** -- catches leaked API keys, tokens, passwords in output 2. **Remote command guard** -- blocks unsafe patterns like `curl | bash` 3. **DB protection** -- prevents destructive SQL (DROP, TRUNCATE, DELETE without WHERE) 4. **Security auto-trigger** -- scans code changes for vulnerabilities as you write 5. **Rate limiting** -- prevents MCP server abuse 6. **MCP usage tracking** -- monitors external tool usage These run automatically as hooks. You don't have to think about them -- they just work. ## The Agent System 11 specialized agents, split by capability: **Opus agents (6)** for deep analysis: - `planner` -- implementation planning for complex features - `architect` -- system design and scalability decisions - `code-reviewer` -- quality, security, maintainability - `security-reviewer` -- OWASP Top 10, secrets, injection detection - `tdd-guide` -- test-driven development enforcement - `database-reviewer` -- PostgreSQL/Supabase optimization **Sonnet agents (5)** for fast execution: - `build-error-resolver` -- fix build errors with minimal diffs - `e2e-runner` -- Playwright E2E test generation - `refactor-cleaner` -- dead code cleanup - `doc-updater` -- documentation updates - `verify-agent` -- fresh-context verification Each agent has its ow
View originalRepository Audit Available
Deep analysis of jina-ai/jina — architecture, costs, security, dependencies & more
Jina AI uses a tiered pricing model. Visit their website for current pricing details.
Key features include: Reader, Embeddings, Reranker.
Jina AI has a public GitHub repository with 21,857 stars.
