agents-coded-rules

A catalog of judgment rules for reviewing Python-based coding agents. It is used after automated checks have found issues that require a person or agent to understand the source code and its behavior.

In plain words
What is it for?
Review agent projects built with frameworks such as LangGraph, LlamaIndex, OpenAI Agents, Google ADK, Pydantic AI, or similar systems, alongside deterministic checks for dependencies, imports, secrets, and packaging.
Why use it?
It covers decisions that simple pattern searches cannot reliably make, such as whether an exception is handled safely, whether dynamic code execution is risky, or whether an agent follows its framework’s conventions.

Agent

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 agents/uipath/skills/agents-coded-rules
Clone the repo
git clone --depth 1 https://github.com/UiPath/skills
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 8,606 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00000 $0.08606
Opus 5 $0.00000 $0.04303
Sonnet 5 $0.00000 $0.01721
Haiku 4.5 $0.00000 $0.00861

Measured 2d ago against content hash 42cef2a8ab6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agents-coded-rules 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 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.

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.

skills/uipath-review/references/agents/agents-coded-rules.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agents — Coded Judgment Rule Catalog

Judgment rules for coded agents (Python — main.py + framework config). Each rule requires the agent to read source and reason — what a regex/AST-emulation/file-walk cannot decide reliably. Same row schema as elsewhere — see ../rule-format.md.

This catalog is judgment-only. Run uip codedagent review "<PROJECT_DIR>" --output json first (SKILL.md Step 2.5) — it returns the deterministic coded findings (pyproject/dependency/python-version gates, import & secret regex, framework symbol existence, bare-except, eval-run analysis, .venv packaging, git-tracked secrets) in the same rule format. Then apply the rules below, which the CLI cannot do.

Read ../rule-format.md and ../rule-catalog-workflow.md first.

Framework detection

Many rules below gate on framework. Detect once and reuse:

Signal Framework
langgraph.json at project root LANGGRAPH
llama_index.json LLAMAINDEX
openai_agents.json OPENAI_AGENTS
google_adk.json GOOGLE_ADK
pydantic_ai.json PYDANTIC_AI
agent_framework.json AGENT_FRAMEWORK
uipath.json with .functions and no framework config above FUNCTION

Rules marked (<FRAMEWORK> only) in trigger skip on other frameworks.

Agent shapes

  • Workflow — one agent, one system prompt (zero for Simple Function), one tool surface, one entry point.
  • Coded workflow — multiple agents in one project; an orchestrator decides which agent handles which input. Detected when create_react_agent(...) is called ≥2 times, or there's a StateGraph supervisor over multiple agents, or OpenAI Agents handoffs=[...] over multiple Agent instances.

Rules in the ## GeneralChecker section tagged (coded_workflow only) skip on single-agent projects.

How to read this file

One H2 section per checker class groups related rules for navigation. Every row's detection_method is the judgment form: read the named source, reason about it, emit when the criteria hold. Log the reasoning in the finding's description. Each section's last row is a CODED_*_ISSUE category bucket — use only when no specific rule fits the observation; do not bend specific rules to use a bucket.

Read the full file on GitHub · 182 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 · 182 lines · 0 tokens per session scan A 42cef2a8ab6f

Subscribe to this mod's changes

agents-coded-rules is an agent published in the GitHub repository UiPath/skills (150 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 8,606 tokens. 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.

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