brand-discovery

brand-discovery is a skill for Claude Code, Codex from ysyecust/everything-claude-code. It costs 80 tokens per session (1,706 once invoked), scanned A, a copy of brand-discovery, MIT.

A structured interview process for discovering and documenting a brand’s identity. It covers areas such as purpose, positioning, audience, personality, voice, and founder perspective across multiple sessions.

In plain words
What is it for?
Running a multi-session brand interview, saving progress between sessions, and producing a complete brandbook for designers, writers, and collaborators.
Why use it?
It turns scattered or unspoken brand knowledge into a reusable reference for consistent decisions and collaboration.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

Part of the ecc plugin — 37 skills, 3 commands, 17 agents 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/ysyecust/everything-claude-code/brand-discovery
Any agent
npx skills add ysyecust/everything-claude-code --skill brand-discovery
Clone the repo
git clone --depth 1 https://github.com/ysyecust/everything-claude-code

Made for: Claude Code, Codex.

Or install ecc, the plugin that ships this one along with the rest of its 37 skills, 3 commands, 17 agents.

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 brand-discovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/ysyecust/everything-claude-code/brand-discovery.svg)](https://agentmods.dev/skills/ysyecust/everything-claude-code/brand-discovery)
Your own site
<a href="https://agentmods.dev/skills/ysyecust/everything-claude-code/brand-discovery"><img src="https://agentmods.dev/badge/skills/ysyecust/everything-claude-code/brand-discovery.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,706 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00080 $0.01706
Opus 5 $0.00040 $0.00853
Sonnet 5 $0.00016 $0.00341
Haiku 4.5 $0.00008 $0.00171

Measured 6d ago against content hash 0c6ef1b72b0f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

brand-discovery 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.

Origin

This is a copy

100% identical to brand-discovery — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/brand-discovery/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Brand Discovery

Use this skill to conduct a structured, adaptive brand identity interview. The goal is a complete 90_SYNTHESIS.md — a master brandbook the organization can use to brief designers, writers, and external collaborators.

The interview runs across multiple sessions. Capture answers to disk as you go so that no elicited knowledge is lost when a conversation ends, and so a later session can resume from where the last one stopped.

When to Activate

  • A brand is being created, repositioned, or needs a written identity reference to brief collaborators.
  • Multiple sessions are expected — the conversation will span days or weeks.
  • Multiple founders or stakeholders need individual interviews before a reconciliation pass.
  • The user wants a structured, repeatable method rather than an ad-hoc chat.
  • Existing brand documentation is scattered, implicit, or founder-dependent and needs to be made explicit.

Session start protocol

On every activation, perform these steps before asking any interview question:

  1. Check for prior progress. Look for an existing set of module files and a state.json checkpoint in the project's brand-identity directory. If none exists, this is a fresh start — confirm the brand name, participants, and where to save the brand-identity files, then begin at the first module.
  2. Read the current module file if one is in progress, and scan its Raw section for previously captured answers.
  3. Report to the user in two or three sentences: which module we are in, its status, and what remains. Then ask: "Continue here, or switch module?"

Interview discipline

Apply these rules throughout every module:

  1. One question at a time. Never present a list of questions.
  2. After each answer: short paraphrase → one deepening probe OR close the thread if the topic is saturated. Never move on silently.
  3. Laddering: for every "what" answer, follow with "Why does that matter to you?" until a core value surfaces (typically two to four iterations).
  4. 5 Whys: for beliefs or positioning claims — push until the root reason, not the surface declaration, is on the table.
  5. Detect thin answers: if generic, jargon-heavy, or vague, ask for one concrete example, a client story, or a number.
  6. Projective techniques (use once per module to break a plateau):
    • "If the brand were a person, how would they walk into a room?"
    • Brand obituary: "If the organization closed in five years, what would customers miss? What would you regret not having said?"
    • Competitive contrast: "Name one peer you admire but would never want to become. What specifically makes them the wrong model?"
  7. Saturation signal: when two consecutive probes produce no new information, summarise and close the module.
  8. End of module: write a structured module file with two sections:
    • ## Raw — verbatim quotes and examples.
    • ## Synthesis — your interpretation, three candidate formulations, open questions, contradictions between participants. Then update the state.json checkpoint (see State protocol below).

Read the full file on GitHub · 146 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. 6d ago First seen · 146 lines · 80 tokens per session scan A 0c6ef1b72b0f

Subscribe to this mod's changes

brand-discovery is a skill published in the GitHub repository ysyecust/everything-claude-code (44 stars, last pushed 19d ago), licensed MIT. It adds 80 tokens to every session and 1,706 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to brand-discovery, differing in 0 lines, and is treated as a copy.

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