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/d-o-hub/github-template-ai-agents/codacynpx skills add d-o-hub/github-template-ai-agents --skill codacygit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWhat 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 | $0.00120 | $0.01506 |
| Opus 5 | $0.00060 | $0.00753 |
| Sonnet 5 | $0.00024 | $0.00301 |
| Haiku 4.5 | $0.00012 | $0.00151 |
Grade A, and why
codacy 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.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Glossary: See glossary.md for shared definitions of Codacy concepts (issues, findings, severity, coverage, tools, patterns, etc.).
Codacy provides two CLI tools:
- Analysis CLI (
codacy-analysis): Runs static analysis locally without pushing code to Codacy Cloud - Cloud CLI (
codacy): Queries remote Codacy data (repositories, issues, PRs, security findings)
Both share credentials at ~/.codacy/credentials. Logging in with either CLI applies to both.
When to Use
- User wants to analyze code locally without pushing to Codacy Cloud
- Need to run CLI-based linting (ESLint, Ruff, Semgrep, RuboCop)
- Scanning staged changes or setting up local Codacy tooling
- User wants to check code quality metrics on Codacy Cloud
- Need to inspect remote PR analysis results or browse vulnerabilities
- Enabling/disabling tools or searching patterns on Codacy Cloud
- Even if they just say "run codacy" or "check code quality"
Setup
# Install Analysis CLI (local analysis)
npm i -g @codacy/analysis-cli
# Install Cloud CLI (remote queries)
npm install -g @codacy/codacy-cloud-cli
# Verify
codacy-analysis --help
codacy --help
Authentication (optional for local, required for cloud)
# Option 1: Interactive login (shared by both CLIs)
codacy login
# Option 2: Token flag
codacy login --token <your-api-token>
# Option 3: Environment variable
export CODACY_API_TOKEN=<your-api-token>
# Obtain tokens: Codacy > My Account > Access Management
# Remove credentials
codacy logout
Shared session: Both CLIs share ~/.codacy/credentials. Logging in/out with either applies to both.
Local Analysis (Analysis CLI)
The Analysis CLI (codacy-analysis) runs static analysis locally. It detects languages, selects tools, and reports issues — without pushing code to Codacy.
Always use --output-format json for structured output in agentic workflows.
Analysis Workflow
1. Initialize configuration
2. Inspect tool availability (dry-run)
3. Install missing dependencies
4. Run analysis
5. Interpret results
What ships with it
14 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.
- evals/evals.json 985 B
- references/analysis-files.md 390 B
- references/analysis-init.md 4.6 KB
- references/analysis-interpret.md 1.0 KB
- references/analysis-logs.md 0 B
- references/analysis-run.md 2.6 KB
- references/analysis-troubleshooting.md 1.7 KB
- references/analysis-workflows.md 1.9 KB
- references/cloud-commands.md 8.3 KB
- references/cloud-workflows.md 807 B
- references/config-format.md 1.0 KB
- references/glossary.md 1.1 KB
- references/output-format.md 925 B
- references/supported-tools.md 1.5 KB
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 · 195 lines · 120 tokens per session scan A 66c626d8796a
codacy is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed 3d ago), licensed MIT. It adds 120 tokens to every session and 1,506 once invoked, about $0.0006 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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