Agent skill

Aidd Riteway AI

by paralleldrive in paralleldrive/aidd

Teaches agents how to write correct riteway ai prompt evals (.sudo files) for multi-step flows that involve tool calls.

MITAuto-check passedAI & LLM Engineering

Install Aidd Riteway AI

skills CLI
$ npx skills add paralleldrive/aidd --skill aidd-riteway-ai -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install paralleldrive/aidd aidd-riteway-ai --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/paralleldrive/aidd.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ai/skills/aidd-riteway-ai .claude/skills/aidd-riteway-ai && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
aidd-riteway-ai
GitHub stars
384
Token cost
~1.6k tokens
SKILL.md length
665 words
Files
3
Skills in repo
35
Repo updated
First seen
Licence
MIT

At a glance

Teaches agents how to write correct riteway ai prompt evals (.sudo files) for multi-step flows that involve tool calls.

  • Works in 7 steps: Read the skill under test and its… → Identify the discrete steps in the… → Create one .sudo eval file per step… → …
  • Writing prompt evals
  • SKILL.md covers Process, Eval File Structure, Rule 1 — One eval file per step and Rule 2 — Unit evals: tell the…, plus 6 more sections
  • Runs JavaScript scripts from its folder

What it does

Aidd Riteway AI is an agent skill from paralleldrive/aidd. Teaches agents how to write correct riteway ai prompt evals (.sudo files) for multi-step flows that involve tool calls. Use when writing prompt evals, creating .sudo test files, or testing agent skills that use tools such as gh, GraphQL, or external APIs.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `README.md` and `riteway-ai.test.js`). Compatibility notes: Requires riteway =9 with the riteway ai subcommand available.

It sits in AI & LLM Engineering, covering LLM evaluation and GraphQL. It works with GraphQL. The repository describes itself as: The standard framework for AI Driven Development. The licence is MIT.

When your agent uses it

  • Writing prompt evals
  • Creating .sudo test files
  • Testing agent skills that use tools such as gh

Example prompts

  • “Use the aidd-riteway-ai skill to teach agents how to write correct riteway ai prompt evals (.sudo files) for multi-step flows that involve tool calls”
  • “/aidd-riteway-ai”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): Requires riteway >=9 with the `riteway ai` subcommand available.

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Read the skill under test and its functional requirements
  2. Identify the discrete steps in the skill's flow
  3. Create one .sudo eval file per step (Rule 1), placed in ai-evals//
  4. For each file, write the userPrompt — include mock tool preambles for unit evals (Rule 2), assert tool calls for step 1 (Rule 3), supply…
  5. Write assertions derived strictly from functional requirements in Given X, should Y format (Rule 7)
  6. Create small, single-condition fixture files as needed (Rule 6)
  7. Verify against the Eval Authoring Checklist below

What it can do on your machine

Read from SKILL.md and the folder at commit 9a7c8e3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (JavaScript), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires riteway >=9 with the `riteway ai` subcommand available.

    From compatibility in the SKILL.md frontmatter.

Context cost

Aidd Riteway AI loads about 1.6k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 665 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from paralleldrive/aidd at commit 9a7c8e3, republished under its MIT licence (© paralleldrive). 665 words, ~1,636 tokens.

Download SKILL.mdSave it as .claude/skills/aidd-riteway-ai/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
aidd-riteway-ai
description
Teaches agents how to write correct riteway ai prompt evals (.sudo files) for multi-step flows that involve tool calls. Use when writing prompt evals, creating .sudo test files, or testing agent skills that use tools such as gh, GraphQL, or external APIs.
compatibility
Requires riteway >=9 with the `riteway ai` subcommand available.

🧪 aidd-riteway-ai

Act as a top-tier AI test engineer to write correct riteway ai prompt evals for multi-step agent skills that involve tool calls.

Refer to /aidd-tdd for assertion style (given/should/actual/expected) and test isolation principles.

Refer to /aidd-requirements for the "Given X, should Y" format when writing assertions inside .sudo eval files.


Process

  1. Read the skill under test and its functional requirements
  2. Identify the discrete steps in the skill's flow
  3. Create one .sudo eval file per step (Rule 1), placed in ai-evals/<skill-name>/
  4. For each file, write the userPrompt — include mock tool preambles for unit evals (Rule 2), assert tool calls for step 1 (Rule 3), supply previous step output for step N > 1 (Rule 4)
  5. Write assertions derived strictly from functional requirements in Given X, should Y format (Rule 7)
  6. Create small, single-condition fixture files as needed (Rule 6)
  7. Verify against the Eval Authoring Checklist below

Eval File Structure

A .sudo eval file has three sections:

import 'ai/skills/<skill-name>/SKILL.md'

userPrompt = """
<prompt sent to the agent under test>
"""

- Given <condition>, should <observable behavior>
- Given <condition>, should <observable behavior>

Assertions are bullet points written after the userPrompt block. Each assertion tests one distinct observable behavior derived from the functional requirements of the skill under test.


Rule 1 — One eval file per step

Given a multi-step flow under test, write one .sudo eval file per step rather than combining all steps into a single overloaded userPrompt.

Naming convention:

ai-evals/<skill-name>/step-1-<description>-test.sudo
ai-evals/<skill-name>/step-2-<description>-test.sudo

Do not collapse multiple steps into one file. Each file tests exactly one discrete agent action.


Rule 2 — Unit evals: tell the agent it is in a test environment

Given a unit eval for a step that involves tool calls (gh, GraphQL, REST API), include a preamble in the userPrompt that:

  1. Tells the prompted agent it is operating in a test environment.
  2. Provides mock tools with stub return values.
  3. Instructs the agent to use the mock tools instead of calling real APIs.

Example preamble:

You have the following mock tools available. Use them instead of real gh or GraphQL calls:

mock gh pr view => returns:
  title: My PR
  branch: feature/foo
  base: main

mock gh api (list review threads) => returns:
  [{ id: "T_01", resolved: false, body: "..." }]

Rule 3 — Step 1: assert tool calls, do not pre-supply answers

Given a unit eval for step 1 of a tool-calling flow, assert that the agent makes the correct tool calls. Do not pre-supply the answers those calls would return — that defeats the purpose of the eval.

Correct pattern for step 1:

userPrompt = """
You have mock tools available. Use them instead of real API calls.
Run step 1 of your skill under test: fetch the PR details and review threads.
"""

- Given mock gh tools, should call gh pr view to retrieve the PR branch name
- Given mock gh tools, should call gh api to list the open review threads
- Given the review threads, should present them before taking any action

Wrong pattern (pre-supplying answers in step 1):

# ❌ Do not do this — it removes the assertion value
userPrompt = """
The PR branch is feature/foo.
The review threads are: [...]
Now generate delegation prompts.
"""

Rule 4 — Step N > 1: supply previous step output as context

Given a unit eval for step N > 1, include the output of the previous step as context inside the userPrompt. This makes each eval independently executable without running the prior steps live.

Example for step 2:

userPrompt = """
You have mock tools available. Use them instead of real calls.

Triage is complete. The following issues remain unresolved:

Issue 1 (thread ID: T_01):
  File: src/utils.js, line 5
  "add() subtracts instead of adding"

Generate delegation prompts for the remaining issues.
"""

Show full SKILL.md (252 more words)Show less

Rule 5 — E2E evals: use real tools, follow -e2e.test.sudo naming

Given an e2e eval, use real tools (no mock preamble) and follow the -e2e.test.sudo naming convention to mirror the project's existing unit/e2e split:

ai-evals/<skill-name>/step-1-<description>-e2e.test.sudo

E2E evals run against live APIs. Only run them when the environment is configured with the necessary credentials.


Rule 6 — Fixture files: small, one condition per file

Given fixture files needed by an eval, keep them small (< 20 lines) with one clear bug or condition per file. Fixtures live in:

ai-evals/<skill-name>/fixtures/<filename>

Example fixture (add.js):

js
export const add = (a, b) => a - b; // bug: subtracts instead of adds

Do not combine multiple bugs in one fixture file. Each fixture must make the assertion conditions unambiguous.


Rule 7 — Assertions: derived from functional requirements only

Given assertions in a .sudo eval, derive them strictly from the functional requirements of the skill under test using the /aidd-requirements format:

- Given <condition>, should <observable behavior>

Include only assertions that test distinct observable behaviors. Do not:

  • Assert implementation details (e.g. internal variable names)
  • Repeat the same observable behavior with different wording
  • Assert things that are implied by another assertion already in the file

Eval Authoring Checklist

Before saving a .sudo eval file, verify:

  • One step per file (Rule 1)
  • Unit evals include mock tool preamble (Rule 2)
  • Step 1 asserts tool calls, not pre-supplied answers (Rule 3)
  • Step N > 1 includes previous step output as context (Rule 4)
  • E2E evals use -e2e.test.sudo suffix (Rule 5)
  • Fixture files are small, one condition each (Rule 6)
  • Assertions derived from functional requirements, no duplicates (Rule 7)

Commands { 🧪 /aidd-riteway-ai - write correct riteway ai prompt evals for multi-step tool-calling flows }

© paralleldrive, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in ai/skills/aidd-riteway-ai of paralleldrive/aidd.

  • SKILL.md
  • README.md
  • riteway-ai.test.js

Open the folder on GitHubat commit 9a7c8e3

Compare with similar skills

Aidd Riteway AI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aidd Riteway AI compared with similar skills
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Aidd Riteway AI this skillparalleldrive/aidd384—~1.6kAutomated safety check: PassMIT
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Phoenix GraphqlArize-ai/phoenix12k—~2.2kAutomated safety check: PassCustom licence
Phoenix CLIArize-ai/phoenix12k—~6.8kAutomated safety check: NotesApache-2.0
Testinginbrainfun/inbrain1421 repos~2kAutomated safety check: PassCustom licence
Agentsop HTTP Tool Wrappingagentsope/SkillAlchemy466—~5.9kAutomated safety check: PassMIT

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Works with

Questions about Aidd Riteway AI

What does Aidd Riteway AI do?

Teaches agents how to write correct riteway ai prompt evals (.sudo files) for multi-step flows that involve tool calls. Aidd Riteway AI is an agent skill from paralleldrive/aidd.sudo files) for multi-step flows that involve tool calls.

When should I use Aidd Riteway AI?

Aidd Riteway AI fits situations like: writing prompt evals; creating .sudo test files; testing agent skills that use tools such as gh.

How do I install Aidd Riteway AI in Claude Code?

Run `npx skills add paralleldrive/aidd --skill aidd-riteway-ai -a claude-code`. Or copy the skill folder (ai/skills/aidd-riteway-ai in paralleldrive/aidd) into .claude/skills/aidd-riteway-ai in your project. Claude Code loads it when a task matches its description.

How do I install Aidd Riteway AI in Codex?

Run `npx skills add paralleldrive/aidd --skill aidd-riteway-ai -a codex`. Or copy the skill folder (ai/skills/aidd-riteway-ai in paralleldrive/aidd) into .agents/skills/aidd-riteway-ai in your project. Codex loads it when a task matches its description.

Can I use Aidd Riteway AI in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add paralleldrive/aidd --skill aidd-riteway-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aidd-riteway-ai, .gemini/skills/aidd-riteway-ai, .github/skills/aidd-riteway-ai and .opencode/skills/aidd-riteway-ai in your project.

What does Aidd Riteway AI need to run?

Going by SKILL.md and its folder, Aidd Riteway AI needs JavaScript for the scripts in its folder. Our summary lists: Node.js. Compatibility (from SKILL.md): Requires riteway >=9 with the `riteway ai` subcommand available..

Does Aidd Riteway AI access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Aidd Riteway AI safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Aidd Riteway AI use?

Aidd Riteway AI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aidd Riteway AI use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Aidd Riteway AI?

Skills that share tags, products or a category with Aidd Riteway AI: Phoenix CLI (github/awesome-copilot, 40k stars), Phoenix Graphql (Arize-ai/phoenix, 12k stars), Phoenix CLI (Arize-ai/phoenix, 12k stars) and Testing (inbrainfun/inbrain, 142 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aidd Riteway AI?

paralleldrive (a GitHub organization) maintains it in paralleldrive/aidd, which has 384 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on June 12, 2026.

Source: paralleldrive/aidd on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.