walkthrough

walkthrough is a skill for Claude Code, Codex from glebis/humane-agentic-design. It costs 164 tokens per session (2,691 once invoked), scanned A, original, MIT.

A usability method that attempts one real task step by step as the person who needs to complete it. It records where the attempt succeeds or breaks.

In plain words
What is it for?
Evaluating a real interface task, asking four questions at each step, and documenting points where users may get stuck.
Why use it?
It tests whether an interface can actually be used for a concrete goal, rather than judging only its appearance or written description.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the humane plugin — 17 skills, 1 agent shipped together

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/glebis/humane-agentic-design/walkthrough
Any agent
npx skills add glebis/humane-agentic-design --skill walkthrough
Clone the repo
git clone --depth 1 https://github.com/glebis/humane-agentic-design

Made for: Claude Code, Codex.

Or install humane, the plugin that ships this one along with the rest of its 17 skills, 1 agent.

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/glebis/humane-agentic-design/walkthrough.svg)](https://agentmods.dev/skills/glebis/humane-agentic-design/walkthrough)
Your own site
<a href="https://agentmods.dev/skills/glebis/humane-agentic-design/walkthrough"><img src="https://agentmods.dev/badge/skills/glebis/humane-agentic-design/walkthrough.svg" alt="Measured on agentmods" height="20"></a>
Per session 164 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,691 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 5.1 $0.00164 $0.02691
Opus 5 $0.00082 $0.01345
Sonnet 5 $0.00033 $0.00538
Haiku 4.5 $0.00016 $0.00269

Measured 6d ago against content hash 43f7686c0739, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, 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 6d 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.

humane/skills/walkthrough/SKILL.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Walkthrough

Announce at start: "I'm using the humane:walkthrough skill to attempt this task as the person who has it."

Inspection asks whether an interface obeys principles. Reaction asks how words land. Neither asks the question that decides whether the product works: can this person, with this goal, get through?

A walkthrough answers that by attempting the task — one concrete task, one concrete person, one step at a time — and recording exactly where the attempt would break.

When to invoke — and when not

Reach for this when you have a task and something to attempt it on.

You want Skill
Can someone complete this task? this skill
Does the interface violate usability principles? nielsen-heuristics
How does this copy land with strangers? respondent-panel
Would an expert stakeholder object to this document? persona-review
Did the change actually improve things? before-after (feed it these results)

Do not run this on a spec or a description. A walkthrough needs something to operate. If all you have is a document, nielsen-heuristics design-risk mode is the honest substitute — say so and switch.

Step 1 — Derive the task from the corpus, not from the interface

The most common way this method fails is walking the flow the designer built instead of the job the person has. Guard against it by taking the task from outside the interface.

  1. Read <corpus_root>/<slug>/jtbd.jsoncorpus_root is the setup setting, default ~/jtbd; read the configured value, not the default. Prefer a task derived from an odi.outcomes[] entry — those already carry a stage (one of define/locate/prepare/confirm/execute/monitor/modify/conclude) and a touch (the surface it lives on). An underserved outcome (high importance, low satisfaction) is the highest-value thing you can walk.
  2. Write the task as the person's goal, in their words, with no interface nouns in it. "Find out what I spent on models last week" — not "open the billing dashboard and apply a date filter." If your task statement names a button, you have already assumed the answer.
  3. Name the actor and their entry state. Who they are, what they already know, what they have already done, where they arrive from, on what device. Use the corpus actor and jtbd.situation. First-time and returning users walk different paths through the same screens — pick one and say which.
  4. State the success condition — the observable thing that is true when the job is done. This is what "task success" is measured against, and it must be decided before the walk.

Read the full file on GitHub · 228 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 6d ago First seen · 228 lines · 164 tokens per session scan A 43f7686c0739

Subscribe to this mod's changes

walkthrough is a skill published in the GitHub repository glebis/humane-agentic-design (27 stars, last pushed 4d ago), licensed MIT. It adds 164 tokens to every session and 2,691 once invoked, about $0.0008 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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