Automated code reviews and suggestions for developer productivity
Codiga is an AI-enhanced code assistant and static analysis platform that provides inline code suggestions, automated linting, and reusable snippet libraries for developers and engineering teams. It’s best suited for individual developers and engineering teams who want to catch security issues, enforce style rules, and accelerate code reviews without large setup costs. Pricing includes a usable free tier and clear paid plans starting from a modest monthly fee for pro use and team collaboration.
Codiga is a developer-focused code assistant that performs static analysis, automated linting, and in-editor code suggestions to help engineers write safer, more consistent code. Its core capability is scanning repositories for security vulnerabilities, code smells, and style violations while offering real-time suggestions and reusable code snippets. Codiga differentiates itself by combining a rules engine with an IDE extension and CI/CD scanners, serving individual developers, open-source maintainers, and engineering teams. Pricing is accessible with a free tier for basic scans and low-cost paid plans for private project limits and team features.
Codiga is a code-assistant and static analysis platform founded to help developers ship higher-quality code through rule-based scanning, automated code suggestions, and snippet libraries. Originating as a developer tooling startup, Codiga positions itself between traditional linters and AI pair programmers by offering both repository scanners and editor integrations. Its core value proposition is reducing manual code review friction: it flags security and quality issues across codebases, enforces coding standards, and surfaces reusable patterns to accelerate development workflows with minimal onboarding.
Codiga’s feature set centers on four concrete capabilities. First, the Code Quality & Security Scanner analyzes repositories to detect OWASP-style vulnerabilities, insecure configurations, and common code smells across languages; it produces line-level findings and categorizations. Second, Editor Extensions for VS Code and JetBrains provide inline suggestions, signature completions, and the ability to insert vetted code snippets from a private or public snippet library. Third, CI/CD integrations let teams run Codiga scans in pipelines (GitHub Actions, GitLab CI), fail builds on critical issues, and post findings as PR comments. Fourth, the Rules and Snippet Engine allows teams to author custom rules (YAML/JSON) and share approved snippets to enforce organization-specific patterns.
Codiga’s pricing is tiered. The Free tier offers a limited number of public and private project scans with basic findings and access to the VS Code extension. The Pro tier (monthly price per user) raises private project scan limits, adds email support, and allows team snippet libraries. The Team/Enterprise tiers (higher monthly or custom pricing) include more concurrent scans, SSO/SAML, on-premises scanning options, and priority support. Exact prices and quotas are published on Codiga’s pricing page and change periodically; the model is freemium with paid tiers for heavier private-project use and enterprise features.
Developers, security engineers, and engineering managers use Codiga in real workflows: a Senior Backend Engineer uses the VS Code extension to reduce insecure patterns by 30% through inline suggestions during development; a Security Analyst runs repository-wide scans to find and triage OWASP risks before releases. It’s also used by open-source maintainers to automate contributor checks and by engineering teams to enforce style rules in CI. For teams wanting purely generative coding (large-language-model completions), Codiga is complementary rather than a direct replacement for tools like GitHub Copilot, focusing more on rule-based scanning and snippet governance.
Three capabilities that set Codiga apart from its nearest competitors.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Limited public and private scans, basic VS Code extension access | Hobbyists and open-source maintainers |
| Pro | €8/month (approx.) | Higher private scan quota, team snippet libraries, email support | Individual professionals and freelancers |
| Team | €24/user/month (approx.) | More concurrent scans, shared rules, CI integration limits raised | Small engineering teams requiring collaboration |
| Enterprise | Custom | SSO/SAML, on-premises scanning, priority support and SLAs | Large orgs needing compliance and scale |
Copy these into Codiga as-is. Each targets a different high-value workflow.
You are a Codiga rules engineer. Create a new static-analysis rule that reliably detects hardcoded AWS IAM secrets and access keys in code (languages: Python, JavaScript, Java). Constraints: use conservative heuristics to minimize false positives, include regex patterns and filename/context checks, and provide a short risk justification. Output format: 1) Rule name, 2) severity (LOW/MEDIUM/HIGH), 3) regex/pattern, 4) code contexts to ignore, 5) one-line remediation suggestion, 6) example vulnerable snippet and fixed snippet. Example vulnerable: "AWS_SECRET_ACCESS_KEY='AKIA...';". Provide the rule ready to paste into Codiga rule format.
You are a DevOps engineer writing a CI snippet. Produce a compact GitHub Actions workflow YAML that runs Codiga static scans on every pull_request for branches matching 'feature/*' and 'bugfix/*'. Constraints: check out code, install Codiga CLI, run full scan, fail PR when HIGH severity issues found, annotate files with findings. Output format: complete workflow YAML, 1-2 sentence explanation of each step, and an example matrix for Node and Python projects. Example: trigger on pull_request with paths: 'src/**'. Keep the workflow < 100 lines and copy-paste ready.
You are a Security Analyst. Given a comma-separated list of repositories and a Codiga JSON scan export for each, produce a prioritized triage table. Constraints: include columns Repo, Finding ID, Severity, Vulnerability Type (OWASP mapping), Likely Exploitability (HIGH/MEDIUM/LOW), Quick Remediation (1-2 lines), Suggested Owner (team role), and ETA for fix. Output format: CSV table sorted by Severity then Exploitability then repo. Additional constraint: include one recommended automation rule (Codiga or CI) to prevent recurrence per top-3 recurring findings. Example input: 'repo-a,repo-b' and sample findings JSON.
You are an engineering lead defining style guardrails. Produce a combined set of 12 JavaScript/TypeScript style rules mapped to ESLint configurations and equivalent Codiga patterns. Constraints: include rules for imports, naming, async/await usage, error handling, max function length, and banned globals; each rule must state rationale, a one-line ESLint rule snippet, Codiga rule outline, and a sample violating snippet with a fixed version. Output format: JSON array where each element has keys: id, rationale, eslint, codiga_pattern, bad_example, fix_example. Ensure rules are team-enforceable and low false-positive risk.
You are a senior application-security engineer. Create a Codiga rule pack to detect SQL injection patterns across Java and Node.js backends. Multi-step: 1) provide 3 rules (parameterized query absence, concatenated SQL strings with user input, risky ORM raw queries) with precise detection logic and false-positive mitigations; 2) include 2 short unit test examples per rule (vulnerable and fixed) in code comments; 3) add an automated quick-fix suggestion or secure snippet developers can insert. Output format: YAML rule pack compatible with Codiga, followed by the test examples and quick-fix snippets. Example few-shot: show one vulnerable concat: "query = 'SELECT * FROM users WHERE id=' + req.query.id" and fixed prepared statement.
You are a Security Program Manager designing an enterprise gating policy for Codiga across 100+ repos. Produce a multi-step implementation playbook: 1) severity thresholds by environment (dev/test/stage/prod), 2) onboarding checklist for teams, 3) automated remediation workflow (scan -> create ticket -> assign -> verify) including example GitHub Actions and ticket template, 4) escalation rules and SLAs, 5) metrics dashboard fields to track. Output format: numbered playbook steps with YAML/JSON snippets for CI and a Markdown ticket template. Include rationales and one change-management tip.
Choose Codiga over Snyk if you prefer combined in-editor suggestions plus CI static scanning with managed snippet governance.
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