Agent skill · Audited from source

Create User Story

skill · huytieu/COG-second-brainMIT licenceAudited 14 Oct 2026 · source 6ea1a6ff2160

★ 1,281pushed 11 days ago
✓SAFEGrade B · 89/100 · 14 Oct 2026 · 6ea1a6f
1,281repo stars · whole huytieu/COG-second-brain

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 6ea1a6ff2160 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)

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Cite this page

ModelsAtlas. “Create User Story (huytieu/COG-second-brain)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/huytieu/create-user-story

Trust audit

Audit 0.4.1 · source read 14 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 6ea1a6ff2160 · 14 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisherhuytieu GitHub userOwner of the repository this skill is read from
  • Source folderhuytieu/COG-second-brain/.claude/skills/create-user-storyThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict6ea1a6ff2160A new audit runs when the source changes
  • Repository statusNot archivedLast push 11 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)

---
name: create-user-story
description: Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)
roles: [product-manager, engineering-lead, founder]
integrations: [linear, github, jira]
---

# COG Create User Story Skill

## When to Invoke
- User wants to create a new user story, feature request, or issue
- User says "create story", "new story", "add issue", "write user story", "create ticket"
- User describes a feature or requirement that should be tracked

## Agent Mode Awareness

**Check `agent_mode` in `00-inbox/MY-PROFILE.md` frontmatter:**
- If `agent_mode: team` — use parallel agents to check for duplicates across all active trackers simultaneously, then create the story
- If `agent_mode: solo` — check duplicates and create the story sequentially in the main conversation

## Command: `/create-user-story`

## Pre-Flight Check

1. **Read `00-inbox/MY-INTEGRATIONS.md`** to determine which project trackers are active:
   - **Linear** — use Linear MCP tools
   - **GitHub** — use `gh` CLI
   - **Jira** — use `jira` CLI or Jira API via WebFetch
   - If NO tracker is active, save the story as a markdown file in `04-projects/[project]/stories/` and inform the user

2. **Read `00-inbox/MY-PROFILE.md`** to get:
   - Active projects (to determine which project/repo/board to target)
   - User's name (for story author attribution)

3. **Ask the user** (if not already provided):
   - What is the feature or requirement? (free-form description)
   - Which project does this belong to? (if multiple active projects)
   - Priority level? (optional — default to medium)

---

## Execution Strategy

### Phase 1: Understand the Request

Parse the user's input to extract:
- **Feature description** — what the user wants built
- **Target users** — who benefits from this
- **Problem statement** — what problem this solves
- **Project context** — which project this belongs to

If the user provides a brief description, ask clarifying questions before proceeding:
- Who is the target user for this feature?
- What problem does this solve?
- Are there any specific acceptance criteria you have in mind?

### Phase 2: Duplicate Check

**CRITICAL: Always check for duplicates before creating.**

#### Team Mode (parallel agents)

Launch duplicate-check agents in parallel using the Task tool with `run_in_background: true`:

**Agent: "duplicate-checker-linear"** (if Linear is active)
```
Search Linear for potential duplicate issues.
1. Use ToolSearch to load Linear tools
2. Use mcp__claude_ai_Linear_2__list_issues to search for issues with similar keywords
3. Search across all active projects/teams
4. Return any issues that match by title similarity or description overlap

Search terms: [extracted keywords from user's description]
Return: list of potential duplicates with title, status, URL, and similarity assessment
```

**Agent: "duplicate-checker-github"** (if GitHub is active)
```
Search GitHub Issues for potential duplicates.
Repository: [CUSTOMIZE: your-org/your-repo]

1. gh search issues "[keywords]" --repo [CUSTOMIZE: your-org/your-repo] --json number,title,state,url,body --limit 20
2. Also search closed issues to check if this was already done:
   gh search issues "[keywords]" --repo [CUSTOMIZE: your-org/your-repo] --state closed --json number,title,state,url --limit 10

Return: list of potential duplicates with title, status, URL, and similarity assessment
```

**Agent: "duplicate-checker-jira"** (if Jira is active)
```
Search Jira for potential duplicate issues.
Project: [CUSTOMIZE: YOUR-PROJECT-KEY]

1. Use WebFetch or jira CLI to search:
   JQL: project = "[CUSTOMIZE: YOUR-PROJECT-KEY]" AND text ~ "[keywords]" ORDER BY created DESC
2. Check both open and recently resolved issues

Return: list of potential duplicates with key, title, status, URL, and similarity assessment
```

#### Solo Mode (sequential)
Run the same duplicate checks sequentially for whichever tracker is active.

### Phase 3: Report Duplicates (if found)

If potential duplicates are found, present them to the user:

```
I found [N] potential duplicate(s):

1. **[TITLE]** ([STATUS]) — [URL]
   Similarity: [High/Medium/Low] — [reason]

2. **[TITLE]** ([STATUS]) — [URL]
   Similarity: [High/Medium/Low] — [reason]

Options:
a) These are different — proceed with creating the new story
b) This is a duplicate of #[N] — skip creation
c) This is related to #[N] — create and link them
```

**Wait for user confirmation before proceeding.**

### Phase 4: Format the User Story

Generate the story in standard user story format:

```markdown
## Title
[Concise, descriptive title]

## User Story
**As a** [type of user],
**I want** [goal/desire],
**So that** [benefit/value].

## Description
[Expanded description of the feature, including context and background]

## Acceptance Criteria

### Scenario 1: [Happy path scenario name]
- **Given** [precondition]
- **When** [action]
- **Then** [expected outcome]

### Scenario 2: [Alternative scenario name]
- **Given** [precondition]
- **When** [action]
- **Then** [expected outcome]

### Scenario 3: [Edge case or error scenario name]
- **Given** [precondition]
- **When** [action]
- **Then** [expected outcome]

## Technical Notes
[Any implementation hints, constraints, or dependencies — if applicable]

## Out of Scope
[What this story explicitly does NOT cover — helps prevent scope creep]
```

**Present the formatted story to the user for review before creating it.**

### Phase 5: Create in Tracker

After user approves the story content:

#### Linear
```
1. Use ToolSearch to load Linear tools
2. Use mcp__claude_ai_Linear_2__get_team to find the target team
3. Use mcp__claude_ai_Linear_2__list_issue_labels to find appropriate labels
4. Use mcp__claude_ai_Linear_2__save_issue to create the issue with:
   - title: [story title]
   - description: [full story in markdown]
   - team: [target team]
   - priority: [user-specified or default medium]
   - labels: [appropriate labels]
```

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 6ea1a6f

Download folder ↗
git clone https://github.com/huytieu/COG-second-brain
git -C COG-second-brain checkout 6ea1a6ff2160

The author documents no install command, so this uses the repository directly. Our verdict covers commit 6ea1a6ff2160 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 6ea1a6ff2160

README badge

For maintainers · shows the latest audit

ModelsAtlas: SAFE BMODELSATLASSAFE · B
[![ModelsAtlas: SAFE B](https://modelsatlas.com/skills/huytieu/create-user-story/badge.svg)](https://modelsatlas.com/skills/huytieu/create-user-story/)

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Questions about Create User Story

What does the Create User Story skill do?
Self-evolving second brain with 35 AI skills, 10 agents, and people CRM. Closed-loop harness: a V-model verification lifecycle where the worker never grades its own homework. Plus paired anti-slop design skills for marketing and product UI. Works with Claude Code, Cursor, Kiro, Gemini CLI, Codex.
Is Create User Story 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 Create User Story 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 (6ea1a6ff2160), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

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