Brand DiscoverySAFE
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Overview
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
8c9f7312d3d6OBSERVED · 2026-10-23What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: brand-discovery
description: Run a structured, resumable multi-session brand identity interview across 8 modules (purpose, positioning, audience, personality, voice, narrative, founder tension) using laddering, 5 Whys, and projective techniques, persisting answers to disk and producing a master brandbook (90_SYNTHESIS.md). Use when creating or repositioning a brand, briefing designers or writers, or making implicit founder knowledge explicit.
---
# 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).
## Module sequence
| File | Label | Frameworks used |
|------|-------|-----------------|
| `10_purpose-why.md` | Purpose / Why | Sinek Golden Circle, Lencioni |
| `20_positioning.md` | Positioning | Dunford "Obviously Awesome", Moore template |
| `30_audience-niche.md` | Audience & Niche | Baker "Business of Expertise", ICP |
| `40_personality-archetype.md` | Personality & Archetype | Mark & Pearson 12 archetypes, J. Aaker 5 dims |
| `50_voice-tone.md` | Voice & Tone | Brand voice guidelines |
| `60_narrative-story.md` | Narrative / Story | Neumeier trueline, brand story arc |
| `70_founder-tension.md` | Founder Brands vs Studio Brand | Enns "Win Without Pitching" |
| `90_SYNTHESIS.md` | Master Brandbook | Kapferer prism, Aaker brand system |
Complete modules in order. Honour a user request to jump modules and note
the skip in `state.json`.
## State write protocol
After each module reaches saturation or done status, write two files:
**Module file** at `modules/{moduleFile}` — full Raw and Synthesis content.
**`state.json`** — a lightweight checkpoint so a later session can resume.
Update `completedModules`, `inProgressModule`, `nextModule`, `lastUpdated`.
Schema:
```json
{
"session": "{brand_name}-brand-{YYYY-MM}",
"outputPath": "{path_to_brand_identity_directory}",
"completedModules": [],
"inProgressModule": "10_purpose-why.md",
"nextModule": "20_positioning.md",
"participants": ["founder-A"],
"lastUpdated": "{ISO-8601}"
}
```
After writing, confirm: "Module X saved. State updated. Next: Y."
**Terminal module (90_SYNTHESIS.md):** when writing the final synthesis,
set `inProgressModule` to `"90_SYNTHESIS.md"` and `nextModule` to `null`
in `state.json`. After writing, set `completedModules` to include
`"90_SYNTHESIS.md"`, then set `inProgressModule` to `null` — leaving it
populated would cause a future resumption to treat the completed brandbook
as still in progress. Confirm: "Brandbook complete. All modules saved."
## Multi-founder mode
When more than one founder participates, write each founder's answers to
`founders/{participant}.md` instead of the main module files. Validate the
`participant` name before writing: accept only alphanumeric characters and
hyphens (e.g. `founder-a`, `anna`); reject names containing path separators
(`/`, `\`, `..`) or special characters. Validate `moduleFile` against the
enTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
8c9f7312d3d6full audit observations/trust-audit/skill/affaan-m__brand-discovery.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-23 | 8c9f7312d3d6 | SAFE | B | 89 | first audit |
Questions
What does the brand-discovery — affaan-m/everything-claude-code skill do?
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Is brand-discovery — affaan-m/everything-claude-code safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can brand-discovery — affaan-m/everything-claude-code access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (8c9f7312d3d6), read on 2026-10-23. The repository is watched, and a new audit runs when it changes — this is the first audit.
Add this badge to your README
Shows this page's audit result and links back to it. It updates when the audit does.
[](https://modelsatlas.com/skills/affaan-m/brand-discovery/)
Not your listing, or something out of date? Claim or update your listing.