ECC: Skill for Codex

.agents/skills/brand-discovery/SKILL.md

brand-discovery is a skill for Codex from affaan-m/ECC. It costs 80 tokens per session (1,706 once invoked), scanned A, original, MIT.

A structured interview process for defining a company's identity, including its purpose, audience, personality, voice, and story. It saves the discussion so work can continue across sessions and stakeholders.

In plain words
What is it for?
Use it to create or reposition a brand, interview founders or stakeholders, and produce a brand book for designers, writers, and other collaborators.
Why use it?
It turns scattered or unspoken brand knowledge into a shared written reference. This reduces reliance on one founder's memory and gives collaborators clearer guidance.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

This is affaan-m/ECC's own configuration. It tells Codex how to work on ECC 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 ECC configures →

Part of the ecc plugin — 70 skills, 58 commands, 68 agents, 1 MCP server shipped together

About the project

ECC is a toolkit that organizes and improves how coding agents work through skills, memory, security checks, research practices, and related extensions. It is for developers using agents such as Claude Code, Codex, OpenCode, and Cursor.

affaan-m/ECC · 255,484 stars · on GitHub · ecc.tools

Reuse

Borrowing it

Nothing to install: this file belongs to affaan-m/ECC. 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/affaan-m/ECC/main/.agents/skills/brand-discovery/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/affaan-m/ECC

Made for: Codex.

Or install ecc, the plugin that ships this one along with the rest of its 70 skills, 58 commands, 68 agents, 1 MCP server.

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/affaan-m/ecc/brand-discovery/github.svg)](https://agentmods.dev/skills/affaan-m/ecc/brand-discovery)
Your own site
<a href="https://agentmods.dev/skills/affaan-m/ecc/brand-discovery"><img src="https://agentmods.dev/badge/skills/affaan-m/ecc/brand-discovery/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 brand-discovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/affaan-m/ecc/brand-discovery"><img src="https://agentmods.dev/badge/skills/affaan-m/ecc/brand-discovery.svg" alt="Reviewed on agentmods" width="80" 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. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Fable 5.1 · 6 Sept 2026 📄 Read the review Third-party audits
  • Socket pass 15 Jun 2026
  • Snyk warn 15 Jun 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00080 $0.01706
Opus 5 $0.00040 $0.00853
Sonnet 5 $0.00016 $0.00341
Haiku 4.5 $0.00008 $0.00171

Measured 11d ago against content hash 0c6ef1b72b0f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, 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 11d 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

Copies of this mod

5 near-identical copies found in the catalogue:

.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. 11d 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 affaan-m/ECC (255,484 stars, last pushed today), 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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