Customer Research
Nexus-JPF/note-companion
When the user wants to conduct, analyze, or synthesize customer research.
Methodology for validating chatbot conversation flow completeness, cycles, and dead ends.
Install Conversation Flow Validator
$ npx skills add revfactory/harness-100 --skill conversation-flow-validator -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install revfactory/harness-100 conversation-flow-validator --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .claude/skills && cp -r skills-src/en/38-chatbot-builder/.claude/skills/conversation-flow-validator .claude/skills/conversation-flow-validator && rm -rf skills-srcUse ~/.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/
Install the "conversation-flow-validator" agent skill from https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validator into .claude/skills/conversation-flow-validator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversation-flow-validator", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validatorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add revfactory/harness-100 --skill conversation-flow-validator -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install revfactory/harness-100 conversation-flow-validator --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .agents/skills && cp -r skills-src/en/38-chatbot-builder/.claude/skills/conversation-flow-validator .agents/skills/conversation-flow-validator && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "conversation-flow-validator" agent skill from https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validator into .agents/skills/conversation-flow-validator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversation-flow-validator", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add revfactory/harness-100 --skill conversation-flow-validator -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install revfactory/harness-100 conversation-flow-validator --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/en/38-chatbot-builder/.claude/skills/conversation-flow-validator .cursor/skills/conversation-flow-validator && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "conversation-flow-validator" agent skill from https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validator into .cursor/skills/conversation-flow-validator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversation-flow-validator", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/revfactory/harness-100.git --path en/38-chatbot-builder/.claude/skills/conversation-flow-validator--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add revfactory/harness-100 --skill conversation-flow-validator -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install revfactory/harness-100 conversation-flow-validator --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/en/38-chatbot-builder/.claude/skills/conversation-flow-validator .gemini/skills/conversation-flow-validator && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "conversation-flow-validator" agent skill from https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validator into .gemini/skills/conversation-flow-validator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversation-flow-validator", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install revfactory/harness-100 conversation-flow-validatorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add revfactory/harness-100 --skill conversation-flow-validator -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .github/skills && cp -r skills-src/en/38-chatbot-builder/.claude/skills/conversation-flow-validator .github/skills/conversation-flow-validator && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "conversation-flow-validator" agent skill from https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validator into .github/skills/conversation-flow-validator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversation-flow-validator", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add revfactory/harness-100 --skill conversation-flow-validator -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install revfactory/harness-100 conversation-flow-validator --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/en/38-chatbot-builder/.claude/skills/conversation-flow-validator .opencode/skills/conversation-flow-validator && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "conversation-flow-validator" agent skill from https://github.com/revfactory/harness-100/tree/main/en/38-chatbot-builder/.claude/skills/conversation-flow-validator into .opencode/skills/conversation-flow-validator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversation-flow-validator", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
conversation-flow-validator- GitHub stars
- 1.3k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 197 words
- Files
- 1
- Skills in repo
- 96
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Methodology for validating chatbot conversation flow completeness, cycles, and dead ends.
- Conversation flow validation
- SKILL.md covers Target Agents, Conversation Flow Graph Analysis, Test Scenario Generation… and Multi-Turn Verification…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Scenario testing
What it does
Conversation Flow Validator is an agent skill from revfactory/harness-100. Methodology for validating chatbot conversation flow completeness, cycles, and dead ends. Use this skill for 'conversation flow validation', 'scenario testing', 'edge case checking', 'fallback verification', 'multi-turn testing', and other dialog quality verification tasks. Note: conducting actual user testing and building A/B testing infrastructure are outside the scope of this skill.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Marketing & SEO, covering A/B testing and User research. The licence is Apache-2.0.
When your agent uses it
- Conversation flow validation
- Scenario testing
- Edge case checking
- Fallback verification
Example prompts
- “conversation flow validation”
- “scenario testing”
- “edge case checking”
- “/conversation-flow-validator”
What it can do on your machine
Read from SKILL.md and the folder at commit 8e8d35c. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
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
Conversation Flow Validator loads about 1.2k tokens when it runs. Until then it costs about 104 tokens; SKILL.md has 197 words of instructions outside code blocks.
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 passed
The automated check found no risky patterns in SKILL.md.
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 revfactory/harness-100 at commit 8e8d35c, republished under its Apache-2.0 licence (© revfactory). 197 words, ~1,242 tokens.
Download SKILL.mdSave it as
.claude/skills/conversation-flow-validator/SKILL.md (or your agent's skills folder).- name
- conversation-flow-validator
- description
- Methodology for validating chatbot conversation flow completeness, cycles, and dead ends. Use this skill for 'conversation flow validation', 'scenario testing', 'edge case checking', 'fallback verification', 'multi-turn testing', and other dialog quality verification tasks. Note: conducting actual user testing and building A/B testing infrastructure are outside the scope of this skill.
Conversation Flow Validator — Dialog Flow Validation Methodology
A skill that enhances dialog quality verification for the dialog-tester and conversation-designer.
Target Agents
- dialog-tester — Systematically validates conversation scenarios
- conversation-designer — Proactively discovers flow defects during the design phase
Conversation Flow Graph Analysis
Node Types
[START] → Entry point
[BOT] → Bot utterance node
[USER] → User input expectation node
[ACTION] → Backend API call
[CONDITION] → Branching condition
[END] → Exit point
[FALLBACK] → Unrecognized input handling
[HANDOFF] → Human agent handoffDefect Type Detection
| Defect | Description | Severity | Detection Method |
|---|---|---|---|
| Dead end | Conversation reaches a dead end | P0 | Search for terminal nodes without END |
| Infinite loop | Infinite cycling through the same nodes | P0 | Cycle detection (DFS) |
| Unreachable | Cannot be reached via any path | P1 | BFS from START for unreached nodes |
| Fallback black hole | No recovery path from fallback | P0 | Verify valid transitions after fallback |
| Slot leakage | Proceeds without collecting required slots | P0 | Track slot fulfillment conditions |
| Context loss | Prior information not retained in multi-turn | P1 | Track session variables |
Test Scenario Generation Framework
Happy Path (Normal Flow)
Purpose: Validate the most common usage flow
Structure:
1. Greeting > Express intent > Provide slots > Confirm > Complete
Example (Cafe order):
USER: "Hello"
BOT: "Hello! How can I help you?"
USER: "I'd like to order two Americanos"
BOT: "Two Americanos, correct? Please choose a size."
USER: "Tall"
BOT: "Two tall Americanos, total $9.00. Would you like to place the order?"
USER: "Yes"
BOT: "Your order has been placed! Thank you."Sad Path (Failure Flow)
Purpose: Validate recovery capabilities in error situations
Scenario types:
1. Ordering unavailable item > Suggest similar items
2. Out of stock > Suggest alternatives or direct to another location
3. API failure > Retry or connect to agent
4. Payment failure > Suggest alternative payment methodsEdge Case (Boundary Cases)
1. Intent switch: Suddenly asking "What are your hours?" mid-order
> Preserve current context, respond, then guide back
2. Multiple intents: "Place an order and send me the receipt too"
> Sequential processing or compound handling
3. Ambiguous expression: "One more of that"
> Reference previous context or ask clarifying question
4. Negative confirmation: Repeated questions after "No"
> Offer alternatives after maximum 2 attempts
5. Empty input / special characters only / emojis only
> Safe fallback responseMulti-Turn Verification Checklist
[ ] Is context maintained in conversations of 3+ turns?
[ ] Can the user modify previously provided information?
[ ] Is there an alternative path after a "No" response?
[ ] Can the original flow be resumed after an intent switch?
[ ] Is there appropriate guidance after session timeout?
[ ] Is escalation triggered after 3 repetitions of the same question?
[ ] When modifying a slot, are other already-collected slots preserved?Fallback Strategy Hierarchy
Level 1: Re-input request
"I'm sorry, I didn't understand that. Could you please say it again?"
> Allowed once
Level 2: Suggest options
"Which of the following would you like? 1. Order 2. View menu 3. Other"
> On 2nd unrecognized input
Level 3: Human agent handoff
"Let me connect you with an agent for more accurate assistance."
> On 3rd unrecognized input or user requestQuality Metrics
| Metric | Formula | Threshold |
|---|---|---|
| Intent recognition rate | Correct recognitions / total utterances | >= 85% |
| Task completion rate | Successful completions / started tasks | >= 70% |
| Fallback rate | Fallback count / total turns | <= 15% |
| Average turn count | Total turns / completed sessions | Task-specific baseline +/- 2 |
| Escalation rate | Agent handoffs / total sessions | <= 20% |
Validation Report Template
## Conversation Flow Validation Report
### Test Summary
- Happy Path: N/M passed
- Sad Path: N/M passed
- Edge Case: N/M passed
### Defects Found
| # | Type | Scenario | Severity | Remediation |
### Fallback Analysis
- Fallback rate: N%
- Key unrecognized utterances: [list]
### Metrics
| Metric | Result | Threshold | Verdict |© revfactory, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in en/38-chatbot-builder/.claude/skills/conversation-flow-validator of revfactory/harness-100.
Open the folder on GitHubat commit 8e8d35c
Compare with similar skills
Conversation Flow Validator 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Conversation Flow Validator this skillrevfactory/harness-100 | 1.3k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Customer ResearchNexus-JPF/note-companion | 870 | 6 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Define Hypothesisproduct-on-purpose/pm-skills | 715 | — | ~966 | Automated safety check: Pass | Apache-2.0 | |
| Reddit Researchlignertys/reddit-research-skills | 1.3k | — | ~3.8k | Automated safety check: Warn | MIT | |
| Design Sprintwondelai/skills | 2.4k | — | ~3.8k | Automated safety check: Pass | MIT | |
| Persona Genemotixco/claude-skills-founder | 517 | — | ~787 | Automated safety check: Pass | MIT |
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product-on-purpose/pm-skills
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Reddit Research
lignertys/reddit-research-skills
Researches what people say on Reddit through semantic search on reddapi.dev: pain points, product validation, competitor research and subreddit trends.
Design Sprint
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Run a structured 5-day process to prototype, test, and validate product ideas with real users.
Persona Gen
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Related
Questions about Conversation Flow Validator
What does Conversation Flow Validator do?
Methodology for validating chatbot conversation flow completeness, cycles, and dead ends. Conversation Flow Validator is an agent skill from revfactory/harness-100. Methodology for validating chatbot conversation flow completeness, cycles, and dead ends.
When should I use Conversation Flow Validator?
Conversation Flow Validator fits situations like: conversation flow validation; scenario testing; edge case checking; fallback verification.
How do I install Conversation Flow Validator in Claude Code?
Run `npx skills add revfactory/harness-100 --skill conversation-flow-validator -a claude-code`. Or copy the skill folder (en/38-chatbot-builder/.claude/skills/conversation-flow-validator in revfactory/harness-100) into .claude/skills/conversation-flow-validator in your project. Claude Code loads it when a task matches its description.
How do I install Conversation Flow Validator in Codex?
Run `npx skills add revfactory/harness-100 --skill conversation-flow-validator -a codex`. Or copy the skill folder (en/38-chatbot-builder/.claude/skills/conversation-flow-validator in revfactory/harness-100) into .agents/skills/conversation-flow-validator in your project. Codex loads it when a task matches its description.
Can I use Conversation Flow Validator 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 revfactory/harness-100 --skill conversation-flow-validator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conversation-flow-validator, .gemini/skills/conversation-flow-validator, .github/skills/conversation-flow-validator and .opencode/skills/conversation-flow-validator in your project.
What does Conversation Flow Validator need to run?
SKILL.md names no scripts, command-line tools or credentials: Conversation Flow Validator is instructions for the agent only.
Does Conversation Flow Validator 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 Conversation Flow Validator safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Conversation Flow Validator use?
Conversation Flow Validator is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Conversation Flow Validator use?
About 1.2k tokens (SKILL.md is roughly 5k 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 Conversation Flow Validator?
Skills that share tags, products or a category with Conversation Flow Validator: Customer Research (Nexus-JPF/note-companion, 870 stars), Define Hypothesis (product-on-purpose/pm-skills, 715 stars), Reddit Research (lignertys/reddit-research-skills, 1.3k stars) and Design Sprint (wondelai/skills, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Conversation Flow Validator?
revfactory (a GitHub user) maintains it in revfactory/harness-100, which has 1,293 GitHub stars. The repository holds 96 skills in this directory. The repository was last updated on March 22, 2026.
Source: revfactory/harness-100 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.