gru-ai: Skill for Claude Code

.claude/skills/walkthrough/SKILL.md

walkthrough is a skill for Claude Code from andrew-yangy/gru-ai. It costs 48 tokens per session (3,251 once invoked), scanned A, original, MIT.

A guided review that simulates real user situations against the current system and compares the intended experience with what actually happens.

In plain words
What is it for?
Use it with a named scenario, all standing scenarios, or a custom situation to trace the user journey and report gaps.
Why use it?
It exposes missing, broken, or surprising parts of a workflow that ordinary code checks may not reveal.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: reads .claude/ paths; names the AskUserQuestion tool.

This is andrew-yangy/gru-ai's own configuration. It tells Claude Code how to work on gru-ai itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything gru-ai configures →

Reuse

Borrowing it

Nothing to install: this file belongs to andrew-yangy/gru-ai. 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/andrew-yangy/gru-ai/main/.claude/skills/walkthrough/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/andrew-yangy/gru-ai

Made for: Claude Code.

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.

agentmods badge for walkthrough

README.md
[![agentmods](https://agentmods.dev/badge/skills/andrew-yangy/gru-ai/walkthrough/github.svg)](https://agentmods.dev/skills/andrew-yangy/gru-ai/walkthrough)
Your own site
<a href="https://agentmods.dev/skills/andrew-yangy/gru-ai/walkthrough"><img src="https://agentmods.dev/badge/skills/andrew-yangy/gru-ai/walkthrough/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.

agentmods 80×15 button for walkthrough

Your own site · 80×15
<a href="https://agentmods.dev/skills/andrew-yangy/gru-ai/walkthrough"><img src="https://agentmods.dev/badge/skills/andrew-yangy/gru-ai/walkthrough.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,251 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.
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 5.1 $0.00048 $0.03251
Opus 5 $0.00024 $0.01625
Sonnet 5 $0.00010 $0.00650
Haiku 4.5 $0.00005 $0.00325

Measured 10d ago against content hash 98d5cbad5625, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

walkthrough 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 10d 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.

.claude/skills/walkthrough/SKILL.md · 371 lines

How it starts

The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Walkthrough — Cognitive Walkthrough

Role Resolution

Read .claude/agent-registry.json to map roles to agent names. Use each agent's id as the subagent_type when spawning. The CPO designs the ideal experience; the CTO traces the actual implementation.


Simulate user scenarios against the current system. Find what's broken, missing, or surprising.

The pattern: For each scenario, design what SHOULD happen (ideal), trace what DOES happen (actual), report the gaps.

Arguments: $ARGUMENTS

  • A specific scenario name (e.g., ceo-runs-directive) → run just that one
  • all → run all standing scenarios
  • A free-text scenario description (e.g., "seller wants to see competitor prices") → ad-hoc walkthrough
  • Empty → list available scenarios and ask which to run

Step 1: Load Scenarios

If $ARGUMENTS is a scenario name or "all":

Read standing scenarios from .context/lessons/scenarios.md.

Each scenario has:

  • Name: slug identifier
  • Actor: who is performing the action (CEO, seller, shopper, developer)
  • Trigger: what starts the flow ("CEO types /directive improve-security")
  • Goal: what the actor wants to achieve
  • Critical path: the steps that MUST work for the scenario to succeed

If all, load all scenarios. If a specific name, load just that one.

If $ARGUMENTS is free text:

Treat it as an ad-hoc scenario. Spawn the CPO to formalize it:

You are the CPO. The CEO described a user scenario informally:

"{$ARGUMENTS}"

Formalize it into this structure:
{
  "name": "slug-name",
  "actor": "who is doing this",
  "trigger": "what starts the flow",
  "goal": "what the actor wants to achieve",
  "critical_path": [
    "Step 1: what should happen first",
    "Step 2: what should happen next",
    ...
  ],
  "success_criteria": "how do you know the scenario succeeded"
}

Think from the ACTOR's perspective, not the system's. What does the actor expect at each step? What would surprise or frustrate them?

CRITICAL OUTPUT FORMAT: First character must be `{`, last must be `}`. JSON only.

Read the full file on GitHub · 371 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. 10d ago First seen · 371 lines · 48 tokens per session scan A 98d5cbad5625

Subscribe to this mod's changes

walkthrough is a skill published in the GitHub repository andrew-yangy/gru-ai (153 stars, last pushed 6mo ago), licensed MIT. It adds 48 tokens to every session and 3,251 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.