What is codacy-review?

A workflow for using Codacy, a code-quality service, both on a local machine and through its cloud dashboard. It can run local analysis and query issues, findings, coverage, pull requests, and review information through Codacy’s command-line tools.

Use it to analyze changed or staged files, inspect Codacy issues and findings, review pull requests, check coverage, or investigate and reduce false positives.

It lets you check code-quality and security problems before or during a change, while combining local results with Codacy’s stored project data.

How rakaarwaky/qwen-web-arwaky configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to rakaarwaky/qwen-web-arwaky. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/rakaarwaky/qwen-web-arwaky/main/.agents/skills/codacy-review/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/rakaarwaky/qwen-web-arwaky

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/rakaarwaky/qwen-web-arwaky/codacy-review/github.svg)](https://agentmods.dev/skills/rakaarwaky/qwen-web-arwaky/codacy-review)

Your own site

<a href="https://agentmods.dev/skills/rakaarwaky/qwen-web-arwaky/codacy-review"><img src="https://agentmods.dev/badge/skills/rakaarwaky/qwen-web-arwaky/codacy-review/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/rakaarwaky/qwen-web-arwaky/codacy-review"><img src="https://agentmods.dev/badge/skills/rakaarwaky/qwen-web-arwaky/codacy-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,148 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00075	$0.01148
Opus 5	$0.00037	$0.00574
Sonnet 5	$0.00015	$0.00230
Haiku 4.5	$0.00007	$0.00115

Measured 12d ago against content hash 370b6434fa3f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

codacy-review 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 12d 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.

.agents/skills/codacy-review/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codacy Review

One skill for the full Codacy workflow: local analysis, cloud queries, and PR review. Two CLIs share credentials at ~/.codacy/credentials:

codacy (Cloud CLI) — remote data: issues, findings, PR analysis, coverage
codacy-analysis (Analysis CLI) — local static analysis without pushing

Prerequisites

codacy info                     # verify Cloud CLI auth
codacy-analysis --help 2>&1 | head -1

Auth: codacy login or export CODACY_API_TOKEN=<token> (token from Codacy > My Account > Access Management > API Tokens). Both CLIs share the same session. Inside a repo, provider/org/repo are auto-detected from the git remote — most commands work with short forms like codacy issues.

Workflow A: Local analysis (before push)

codacy-analysis init --default              # first time only; merges .codacy.yaml excludes
codacy-analysis analyze --pr --output-format json          # changes vs PR target branch
codacy-analysis analyze --diff --output-format json        # changes vs merge base
codacy-analysis analyze --staged --output-format json      # staged only
codacy-analysis analyze --tool Ruff --files "src/**/*.ts" --output-format json

Use --install-dependencies to fetch missing tool binaries (installed under ~/.codacy/). Exit codes: 0 = clean, 1 = issues found, 2 = execution error. Parse .issues[] with severity/file; check .capability.unavailable for tools only available in Cloud.

Workflow B: Cloud queries & dashboard

codacy info                                        # account / orgs
codacy issues --overview                           # totals by category/severity/language + noise suggestions
codacy issues --severities Critical,High           # filter: --branch --patterns --categories --tools --authors
codacy issue <issueId>                             # single issue detail (pattern docs + code context)
codacy findings --severities Critical,High         # security findings (SAST/SCA/Secrets)
codacy finding <findingId>                         # single finding (CVE data, affected functions)
codacy repository                                  # dashboard: metrics, PRs, issues
codacy repository --reanalyze-and-wait             # trigger reanalysis, block until done
codacy tools / codacy patterns <tool>              # inspect enabled tools/patterns

Read the full file on GitHub · 84 lines

Changes

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.

12d ago First seen · 84 lines · 75 tokens per session scan A 370b6434fa3f

Subscribe to this mod's changes

codacy-review is a skill published in the GitHub repository rakaarwaky/qwen-web-arwaky (14 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 1,148 once invoked, about $0.0004 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 2026-08-30.

Code review

autoreview

Pre-commit/ship code review: Codex default; optional Claude or Pi.

openclaw/clawhub · 20 tokens

omh-code-review

This is a Hermes-native code-review workflow skill.

rlaope/oh-my-hermes · 46 tokens

revdiff-plan

Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…

umputun/revdiff · 84 tokens

code-reviewer

Code review specialist focused on patterns, bugs, security, and performance.

RightNow-AI/openfang · 17 tokens

full-repo-review

Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.

notque/vexjoy-agent · 22 tokens

agent-teams-simplify-and-harden

Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…

LeoYeAI/openclaw-master-skills · 115 tokens

qwen-web-arwaky: Skill for Claude Code