agentmods.dev

hf.audit-code

A repository-wide code review that looks for dead code, hard-to-follow code, duplication, weak error handling, type-safety problems, and design issues.

In plain words
What is it for?
Use it to inspect Python source files across a repository and create assigned, labelled GitHub issues for each finding.
Why use it?
It gathers common code-quality problems in one review and records the findings as GitHub issues for later processing.

Skill for Claude CodeCodex

5 2d ago A scan 7 tokens original Apache-2.0
View the source file T-rav/hydraflow
Install

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.

agentmods
npx agentmods add skills/t-rav/hydraflow/hf.audit-code
Any agent
npx skills add T-rav/hydraflow --skill hf.audit-code
Clone the repo
git clone --depth 1 https://github.com/T-rav/hydraflow

Made for: Claude Code, Codex.

Per session 7 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,928 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00007 $0.03928
Opus 5 $0.00003 $0.01964
Sonnet 5 $0.00001 $0.00786
Haiku 4.5 $0.00001 $0.00393

Measured 2d ago against content hash 1415ca494b98, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

hf.audit-code scanned grade A with 1 finding 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 2d 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- Do they have timeouts? (subprocess.run without timeout, asyncio without timeout)
.codex/skills/hf.audit-code/SKILL.md · 357 lines

How it starts

The opening of the file, as written. The whole thing — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Quality Audit

Run a comprehensive code quality audit across the entire repo. Dynamically analyzes source code for dead code, complexity, duplication, error handling gaps, type safety issues, and architectural problems. Creates GitHub issues for findings so HydraFlow can process them.

Instructions

  1. Resolve configuration before doing anything else:

    • Run echo "$HYDRAFLOW_GITHUB_REPO" — if set, use it as the target repo (e.g., owner/repo). If empty, run git remote get-url origin and extract the owner/repo slug (strip https://github.com/ prefix and .git suffix).
    • Run echo "$HYDRAFLOW_GITHUB_ASSIGNEE" — if set, use it as the issue assignee. If empty, extract the owner from the repo slug (the part before /).
    • Use hydraflow-plan as the label for created issues.
    • Store resolved values as $REPO, $ASSIGNEE, $LABEL.

  2. Discover project structure:

    • Use Glob to find all *.py source files, excluding .venv/, venv/, __pycache__/, node_modules/, dist/, build/.
    • Separate into SOURCE files (production code) and TEST files (anything under tests/ or matching test_*.py).
    • Count total source files, total lines, and identify the main modules.

  3. Launch agents in parallel using Task with run_in_background: true and subagent_type: "general-purpose":

    • Agent 1: Dead code & unused exports — Finds unreachable code, unused functions, unused imports, and stale modules.
    • Agent 2: Complexity & duplication — Finds overly complex functions, duplicated logic, and DRY violations.
    • Agent 3: Error handling & robustness — Finds bare excepts, swallowed errors, missing error paths, and fragile patterns.
    • Agent 4: Type safety & API consistency — Finds missing type annotations, Any overuse, inconsistent return types, and public API gaps.

  4. Wait for all agents to complete.

  5. After all finish, run gh issue list --repo $REPO --label $LABEL --state open --search "code quality" --limit 200 to show the user a final summary of all issues created.

Read the full file on GitHub · 357 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.

  1. 2d ago First seen · 357 lines · 7 tokens per session scan A 1415ca494b98

Subscribe to this mod's changes

hf.audit-code is a skill published in the GitHub repository T-rav/hydraflow (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 7 tokens to every session and 3,928 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Code reviewagentic-developmentagentic-workflowwishful-programming
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