ci

A setup tool that creates a GitHub Actions workflow for running coder-eval, a system that tests coding agents on prepared tasks. The workflow can run checks on pull requests or on a schedule, using the published action.

In plain words
What is it for?
Use it to make evaluation runs block unsuitable changes or run regularly to detect when an agent or task suite starts performing worse.
Why use it?
It removes the manual work of connecting agent credentials, test output, and minimum score requirements to continuous integration, the automated checks that run for code changes.

Skill for Claude CodeCodex

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/uipath/coder_eval/ci
Any agent
npx skills add UiPath/coder_eval --skill ci
Clone the repo
git clone --depth 1 https://github.com/UiPath/coder_eval

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,626 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 $0.00045 $0.02626
Opus 5 $0.00023 $0.01313
Sonnet 5 $0.00009 $0.00525
Haiku 4.5 $0.00005 $0.00263

Measured yesterday against content hash 7ead73404028, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ci 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 yesterday.

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.

plugins/coder-eval/skills/ci/SKILL.md · 234 lines

How it starts

The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Wire coder-eval into GitHub Actions

The user's request is: $ARGUMENTS

Step 1 — Check the repository

Find the repository's task tree by following ${CLAUDE_PLUGIN_ROOT}/reference/repo-layout.md, and check whether .github/workflows/ exists. The paths you resolve here become the workflow's tasks: input in step 3 — that input is written from discovery, never from a fixed guess.

If there is no .github/ directory at all, say that this skill targets GitHub Actions and stop — do not invent an equivalent for another CI system unless the user asks.

If a workflow already runs coder-eval (grep the workflows for coder_eval), do not add a second one. Show what is there and offer to update it.

Step 2 — Choose the trigger

Ask, or infer from the request:

  • On pull request — gate changes to the tasks or to whatever they exercise.
  • On a schedule — the skill-drift case: re-run the suite weekly against the current model so a skill that quietly stops triggering surfaces before users hit it. This is the trigger most repositories actually want, and the one they forget. If the suite is an activation suite, the environment note in step 3 is not optional for this trigger — without it the scheduled run reports total drift every week regardless of whether anything drifted.
  • Both, which is fine — one workflow, two on: keys.

Step 3 — Emit the workflow

The composite action installs the coder-eval CLI and nothing else: it is agent-agnostic and installs no coding-agent runtime. A task using the default claude-code agent therefore needs Node plus the Claude CLI provided by the job first, or the run dies on a missing claude binary. There is no Marketplace install step for the action itself, but those two prerequisite steps are not optional.

name: Coder Eval

on:
  pull_request:
  schedule:
    - cron: "0 6 * * 1"   # Mondays 06:00 UTC — catches model/skill drift

# Least privilege: this job runs agent-generated code, so it gets no write scope.
permissions:
  contents: read

jobs:
  eval:
    runs-on: ubuntu-latest
    timeout-minutes: 30
    steps:
      - uses: actions/checkout@v6
        with:
          # Do not leave a credentialed .git/config in a workspace where
          # agent-generated code runs.
          persist-credentials: false

      # The action installs no coding-agent runtime — provide it here.
      - uses: actions/setup-node@v4
        with:
          node-version: "20"
      - run: npm install -g @anthropic-ai/claude-code

      - uses: UiPath/coder_eval@v0
        with:
          tasks: tasks/*.yaml
          model: claude-haiku-4-5-20251001
          junit-path: runs/ci/junit.xml
          step-summary: true
          minimum-task-score: "0.7"
          env: |
            ANTHROPIC_API_KEY=${{ secrets.ANTHROPIC_API_KEY }}

Read the full file on GitHub · 234 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. yesterday First seen · 234 lines · 45 tokens per session scan A 7ead73404028

Subscribe to this mod's changes

ci is a skill published in the GitHub repository UiPath/coder_eval (119 stars, last pushed 3d ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,626 once invoked, about $0.0002 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.

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