New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Echo Segment

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination.

MITAuto-check: notesSales & Support

Install Echo Segment

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill echo-segment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace echo-segment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ai-agency/tonone/skills/echo-segment .claude/skills/echo-segment && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
echo-segment
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
343 words
Files
2
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination.

  • Works in 6 steps: Collect Raw Signals → Identify Behavioral Clusters → Build Persona Cards → …
  • Asked to build personas
  • SKILL.md covers Steps and Delivery
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Echo Segment is an agent skill from jeremylongshore/tons-of-skills-marketplace. User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination. Use when asked to "build personas", "who are our users", "segment our users", "create user profiles", "define user archetypes", or "who is the target user".

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `.claude-plugin/plugin.json`).

It sits in Sales & Support, covering Customer support. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Asked to build personas
  • Who are our users
  • Segment our users
  • Create user profiles

Example prompts

  • “build personas”
  • “who are our users”
  • “segment our users”
  • “/echo-segment”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Collect Raw Signals
  2. Identify Behavioral Clusters
  3. Build Persona Cards
  4. Write a Counter-Persona
  5. Validate Assumptions
  6. Present Personas

What it can do on your machine

Read from SKILL.md and the folder at commit 23ea8d4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep
    • WebFetch
    • WebSearch
    • Task
    • TodoWrite

    …and 1 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Echo Segment loads about 1.1k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 343 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit 23ea8d4, republished under its MIT licence (© jeremylongshore). 343 words, ~1,058 tokens.

Download SKILL.mdSave it as .claude/skills/echo-segment/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
echo-segment
description
User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination. Use when asked to "build personas", "who are our users", "segment our users", "create user profiles", "define user archetypes", or "who is the target user".
allowed-tools
Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion
version
0.6.4
author
tonone-ai <hello@tonone.ai>
license
MIT

User Segmentation and Personas

You are Echo — the user researcher on the Product Team. Build personas from evidence, not assumptions.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 1: Collect Raw Signals

Identify available data sources:

SourceWhat to look for
AnalyticsHigh-engagement segments, power users, activation patterns by cohort
CRM / user recordsIndustry, company size, role, plan tier, tenure
Support ticketsWho is asking for help and about what
NPS verbatimsWho gives 9-10 (promoters) vs 0-6 (detractors) and why
Churn dataWho cancels and what reason they give
App store / G2 reviewsWho leaves reviews and what they praise or criticize

Ask user to provide any of these inputs, or scan for them in the codebase (user model, analytics events, support tool configs).

Step 2: Identify Behavioral Clusters

Look for patterns across the data:

  • By job / role — who uses the product professionally vs casually?
  • By use case — what primary job-to-be-done brings them to the product?
  • By engagement level — power users vs occasional users vs at-risk users
  • By outcome — who succeeds (achieves their goal) vs who struggles?

Aim for 2-4 segments. More than 4 is usually noise — collapse similar clusters.

Step 3: Build Persona Cards

For each segment, write a persona card:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[Name] — [Role/Archetype]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

PROFILE
  Industry:   [industry]
  Role:       [job title]
  Company:    [size / type]
  Tenure:     [how long they've been a user]

PRIMARY JOB-TO-BE-DONE
  [One sentence: "When [situation], I want to [motivation] so I can [outcome]"]

WHAT THEY SAY        │ WHAT THEY MEAN
─────────────────────┼────────────────────────────
"[quote from tickets │ [underlying need behind
 or NPS verbatims]"  │  the quote]

TOP FRUSTRATIONS
  1. [friction that causes churn or complaints]
  2. [friction]
  3. [friction]

WHAT SUCCESS LOOKS LIKE FOR THEM
  [How they would describe a win using your product]

DATA SOURCE
  [which data points this persona is based on — be honest about sample size]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 4: Write a Counter-Persona

Describe the user this product is explicitly NOT for:

NOT FOR: [archetype]
Why they come: [why they find the product initially]
Why they leave / fail: [why the product doesn't serve them]
Risk: [the danger of designing for them — feature bloat, positioning confusion]
Step 5: Validate Assumptions

For each persona, flag how much evidence backs it:

  • High confidence — based on 10+ interviews, significant analytics data, or clear CRM pattern
  • Medium confidence — based on a few data points, directional only
  • Assumed — hypothesis without data — needs validation before product decisions are made on it
Step 6: Present Personas

Present each persona card, then the counter-persona, then a brief recommendation: "Design primarily for [Persona A]. [Persona B] is valuable but secondary."

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in plugins/ai-agency/tonone/skills/echo-segment of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • .claude-plugin/plugin.json

Open the folder on GitHubat commit 23ea8d4

Compare with similar skills

Echo Segment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Echo Segment compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Echo Segment this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: NotesMIT
Siftranknoperator/siftrank224—~2.9kAutomated safety check: PassMIT
Supporthaacked/dotfiles134—~2.9kAutomated safety check: PassNone
Customer Support Agentmastra-ai/mastra29k—~2.2kAutomated safety check: PassCustom licence
Add Agent Adaptersafedep/gryph172—~679Automated safety check: PassApache-2.0
Agent Support Matrixjazzyalex/agent-sessions893—~587Automated safety check: PassMIT

Similar skills

  • Siftrank

    noperator/siftrank

    Find needles in haystacks with SiftRank. An agent skill from noperator/siftrank.

    224 GitHub stars~2.9k tokensUpdated 18 days ago
    Sales & SupportAuto-check passed

  • Support

    haacked/dotfiles

    Support hero workflow — start a ticket investigation with auto-organized notes, find existing notes, or generate the weekly highlights log.

    134 GitHub stars~2.9k tokensUpdated today
    Sales & SupportAuto-check passed

  • Customer Support Agent

    mastra-ai/mastra

    Authoring playbook for building agents that triage and reply to customer messages — support tickets, email inquiries, chat questions, refund requests, or product issues.

    29k GitHub stars~2.2k tokensUpdated today
    Sales & SupportAuto-check passed

  • Add Agent Adapter

    safedep/gryph

    A skill your agent uses when adding support for a new AI coding agent to Gryph, or when changing how an existing agent adapter is wired.

    172 GitHub stars~679 tokensUpdated 3 days ago
    Sales & SupportAuto-check passed

  • Agent Support Matrix

    jazzyalex/agent-sessions

    Maintain Agent Sessions agent support matrix and JSON/JSONL parsing compatibility.

    893 GitHub stars~587 tokensUpdated today
    Sales & SupportAuto-check passed

  • Company Brain Company QA

    topoteretes/cognee

    Build one company memory from a SQL database, a support ticket export and a folder of documents, linked into one graph by cognee, then answer questions that need several of those sources together.

    32k GitHub stars~750 tokensUpdated yesterday
    Sales & SupportAuto-check: notes

More from jeremylongshore/tons-of-skills-marketplace

All 3,342 skills in this repo

  • Performing Security Code Review

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.

    2.8k GitHub starsUsed in 2 repos~1.3k tokens
    Auto-check: notes

  • Analyzing Text With NLP

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to perform natural language processing and text analysis using the nlp-text-analyzer plugin.

    2.8k GitHub starsUsed in 1 repo~819 tokens
    Auto-check passed

  • Building Neural Networks

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill allows AI assistant to construct and configure neural network architectures using the neural-network-builder plugin.

    2.8k GitHub starsUsed in 1 repo~1k tokens
    Auto-check passed

  • Detecting Data Anomalies

    jeremylongshore/tons-of-skills-marketplace

    Process identify anomalies and outliers in datasets using machine learning algorithms.

    2.8k GitHub starsUsed in 1 repo~1.4k tokens
    Auto-check passed

  • Explaining Machine Learning Models

    jeremylongshore/tons-of-skills-marketplace

    Build this skill enables AI assistant to provide interpretability and explainability for machine learning models.

    2.8k GitHub starsUsed in 1 repo~1k tokens
    Auto-check passed

  • Optimizing Prompts

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill optimizes prompts for large language models (llms) to reduce token usage, lower costs, and improve performance.

    2.8k GitHub starsUsed in 1 repo~1k tokens
    Auto-check passed

Categories

Questions about Echo Segment

What does Echo Segment do?

User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination. Echo Segment is an agent skill from jeremylongshore/tons-of-skills-marketplace. User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination.

When should I use Echo Segment?

Echo Segment fits situations like: asked to build personas; who are our users; segment our users; create user profiles.

How do I install Echo Segment in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill echo-segment -a claude-code`. Or copy the skill folder (plugins/ai-agency/tonone/skills/echo-segment in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/echo-segment in your project. Claude Code loads it when a task matches its description.

How do I install Echo Segment in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill echo-segment -a codex`. Or copy the skill folder (plugins/ai-agency/tonone/skills/echo-segment in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/echo-segment in your project. Codex loads it when a task matches its description.

Can I use Echo Segment in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill echo-segment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/echo-segment, .gemini/skills/echo-segment, .github/skills/echo-segment and .opencode/skills/echo-segment in your project.

What does Echo Segment need to run?

SKILL.md names no scripts, command-line tools or credentials: Echo Segment is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion.

Does Echo Segment access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Echo Segment safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Echo Segment use?

Echo Segment is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Echo Segment use?

About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Echo Segment?

Skills that share tags, products or a category with Echo Segment: Siftrank (noperator/siftrank, 224 stars), Support (haacked/dotfiles, 134 stars), Customer Support Agent (mastra-ai/mastra, 29k stars) and Add Agent Adapter (safedep/gryph, 172 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Echo Segment?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,821 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 8, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.