User Story Writer
deanpeters/Product-Manager-Skills
Writes user stories in Mike Cohn's format with Gherkin acceptance criteria, turning user needs into development-ready work with testable conditions.
A skill your agent uses when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
Install Qcsd Refinement Swarm
$ npx skills add proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-refinement-swarm --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/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/assets/skills/qcsd-refinement-swarm .claude/skills/qcsd-refinement-swarm && 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 "qcsd-refinement-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarm into .claude/skills/qcsd-refinement-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-refinement-swarm", 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/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarmType 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 proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-refinement-swarm --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .agents/skills && cp -r skills-src/assets/skills/qcsd-refinement-swarm .agents/skills/qcsd-refinement-swarm && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "qcsd-refinement-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarm into .agents/skills/qcsd-refinement-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-refinement-swarm", 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 proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-refinement-swarm --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/assets/skills/qcsd-refinement-swarm .cursor/skills/qcsd-refinement-swarm && 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 "qcsd-refinement-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarm into .cursor/skills/qcsd-refinement-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-refinement-swarm", 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/proffesor-for-testing/agentic-qe.git --path assets/skills/qcsd-refinement-swarm--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 proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-refinement-swarm --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/assets/skills/qcsd-refinement-swarm .gemini/skills/qcsd-refinement-swarm && 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 "qcsd-refinement-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarm into .gemini/skills/qcsd-refinement-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-refinement-swarm", 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 proffesor-for-testing/agentic-qe qcsd-refinement-swarmInstalls 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 proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .github/skills && cp -r skills-src/assets/skills/qcsd-refinement-swarm .github/skills/qcsd-refinement-swarm && 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 "qcsd-refinement-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarm into .github/skills/qcsd-refinement-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-refinement-swarm", 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 proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-refinement-swarm --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/assets/skills/qcsd-refinement-swarm .opencode/skills/qcsd-refinement-swarm && 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 "qcsd-refinement-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-refinement-swarm into .opencode/skills/qcsd-refinement-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-refinement-swarm", 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
qcsd-refinement-swarm- GitHub stars
- 495
- Token cost
- ~1.5k tokens
- SKILL.md length
- 408 words
- Files
- 13 (incl. scripts)
- Skills in repo
- 93
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
- Works in 9 steps: Flag Detection --… → Core Agents -- steps/02-core-agents.md… → Batch 1 Results --… → …
- Running Sprint Refinement sessions with SFDIPOT product factors
- SKILL.md covers Overview, ENFORCEMENT RULES - READ FIRST, Step Execution Protocol and Agent Inventory, plus 1 more section
- Generating BDD scenarios
What it does
Qcsd Refinement Swarm is an agent skill from proffesor-for-testing/agentic-qe. Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts (for example `evals/qcsd-refinement-swarm.yaml`, `schemas/output.json` and `scripts/validate-config.json`).
It sits in Product & Project Management. The repository describes itself as: Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support… The licence is MIT.
When your agent uses it
- Running Sprint Refinement sessions with SFDIPOT product factors
- Generating BDD scenarios
- Validating requirements in the QCSD Refinement phase
Example prompts
- “/qcsd-refinement-swarm”
Workflow steps
9 steps, taken from the first numbered list in SKILL.md.
- Flag Detection -- steps/01-flag-detection.md -- Analyze story content, evaluate all 7 flags
- Core Agents -- steps/02-core-agents.md -- Spawn qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator
- Batch 1 Results -- steps/03-batch1-results.md -- Wait and extract metrics
- Conditional Agents -- steps/04-conditional-agents.md -- Spawn flagged agents
- Decision Synthesis -- steps/05-decision-synthesis.md -- Apply READY/CONDITIONAL/NOT-READY logic
- Report Generation -- steps/06-report-generation.md -- Generate refinement report
- Learning Persistence -- steps/07-learning-persistence.md -- Store findings to memory
- Transformation -- steps/08-transformation.md -- Run test idea rewriter on all test ideas
- Final Output -- steps/09-final-output.md -- Display completion summary
What it can do on your machine
Read from SKILL.md and the folder at commit 829d030. 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
Ships 1 file in scripts/, which the agent can run.
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
Qcsd Refinement Swarm loads about 1.5k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 408 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); the scripts in this folder are not scanned.
SKILL.md
The full file from proffesor-for-testing/agentic-qe at commit 829d030, republished under its MIT licence (© proffesor-for-testing). 408 words, ~1,456 tokens.
Download SKILL.mdSave it as
.claude/skills/qcsd-refinement-swarm/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.- name
- qcsd-refinement-swarm
- description
- Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
- category
- qcsd-phases
- priority
- critical
- version
- 1.0.0
- tokenEstimate
- 3200
- agents.core
- qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator
- agents.conditional
- qe-contract-validator, qe-impact-analyzer, qe-dependency-mapper, qe-middleware-validator, qe-odata-contract-tester, qe-sod-analyzer
- agents.transformation
- qe-test-idea-rewriter
- agents.total
- 10
- agents.sub_agents
- 0
- skills
- context-driven-testing, testability-scoring, risk-based-testing
QCSD Refinement Swarm v1.0
Shift-left quality engineering swarm for Sprint Refinement sessions.
Overview
The Refinement Swarm takes user stories that passed Ideation and prepares them for Sprint commitment using SFDIPOT product factors, BDD scenarios, and INVEST validation. It renders a READY / CONDITIONAL / NOT-READY decision.
QCSD Phase Positioning
| Phase | Swarm | Decision | When |
|---|---|---|---|
| Ideation | qcsd-ideation-swarm | GO / CONDITIONAL / NO-GO | PI/Sprint Planning |
| Refinement | qcsd-refinement-swarm | READY / CONDITIONAL / NOT-READY | Sprint Refinement |
| Development | qcsd-development-swarm | SHIP / CONDITIONAL / HOLD | During Sprint |
| Verification | qcsd-cicd-swarm | RELEASE / REMEDIATE / BLOCK | Pre-Release / CI-CD |
| Production | qcsd-production-swarm | HEALTHY / DEGRADED / CRITICAL | Post-Release |
Parameters
STORY_CONTENT: User story with acceptance criteria (required)OUTPUT_FOLDER: Where to save reports (default:${PROJECT_ROOT}/Agentic QCSD/refinement/)
ENFORCEMENT RULES - READ FIRST
| Rule | Enforcement |
|---|---|
| E1 | MUST spawn ALL THREE core agents in Step 2. |
| E2 | MUST put all parallel Task calls in a SINGLE message. |
| E3 | MUST STOP and WAIT after each batch. |
| E4 | MUST spawn conditional agents if flags are TRUE. |
| E5 | MUST apply READY/CONDITIONAL/NOT-READY logic exactly. |
| E6 | MUST generate the full report structure. |
| E7 | Each agent MUST read its reference files before analysis. |
| E8 | MUST apply qe-test-idea-rewriter transformation in Step 8. |
| E9 | MUST execute Step 7 learning persistence. |
Step Execution Protocol
Execute steps sequentially by reading each step file with the Read tool.
Steps
- Flag Detection --
steps/01-flag-detection.md-- Analyze story content, evaluate all 7 flags - Core Agents --
steps/02-core-agents.md-- Spawn qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator - Batch 1 Results --
steps/03-batch1-results.md-- Wait and extract metrics - Conditional Agents --
steps/04-conditional-agents.md-- Spawn flagged agents - Decision Synthesis --
steps/05-decision-synthesis.md-- Apply READY/CONDITIONAL/NOT-READY logic - Report Generation --
steps/06-report-generation.md-- Generate refinement report - Learning Persistence --
steps/07-learning-persistence.md-- Store findings to memory - Transformation --
steps/08-transformation.md-- Run test idea rewriter on all test ideas - Final Output --
steps/09-final-output.md-- Display completion summary
Show full SKILL.md (134 more words)Show less
Execution Instructions
- Use the Read tool to load the current step file
- Execute the step's instructions completely
- Verify all success criteria are met
- Pass output as context to next step
- If a step fails, halt and report
Resume Support
To resume from a specific step: specify --from-step N.
Agent Inventory
| Agent | Type | Domain | Batch |
|---|---|---|---|
| qe-product-factors-assessor | Core | requirements-validation | 1 |
| qe-bdd-generator | Core | requirements-validation | 1 |
| qe-requirements-validator | Core | requirements-validation | 1 |
| qe-contract-validator | Conditional (HAS_API) | contract-testing | 2 |
| qe-impact-analyzer | Conditional (HAS_REFACTORING) | code-intelligence | 2 |
| qe-dependency-mapper | Conditional (HAS_DEPENDENCIES) | code-intelligence | 2 |
| qe-middleware-validator | Conditional (HAS_MIDDLEWARE) | enterprise-integration | 2 |
| qe-odata-contract-tester | Conditional (HAS_SAP_INTEGRATION) | enterprise-integration | 2 |
| qe-sod-analyzer | Conditional (HAS_AUTHORIZATION) | enterprise-integration | 2 |
| qe-test-idea-rewriter | Transformation (always) | test-generation | 3 |
Total: 10 agents (3 core + 6 conditional + 1 transformation)
Key Principle
Refinement quality determines sprint success. This swarm ensures stories are testable, complete, and ready for development commitment.
© proffesor-for-testing, 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 12 other files (scripts) in assets/skills/qcsd-refinement-swarm of proffesor-for-testing/agentic-qe.
- SKILL.md
- evals/qcsd-refinement-swarm.yaml
- schemas/output.json
- scripts/validate-config.json
- steps/01-flag-detection.md
- steps/02-core-agents.md
- steps/03-batch1-results.md
- steps/04-conditional-agents.md
- steps/05-decision-synthesis.md
- steps/06-report-generation.md
- steps/07-learning-persistence.md
- steps/08-transformation.md
- steps/09-final-output.md
Open the folder on GitHubat commit 829d030
Compare with similar skills
Qcsd Refinement Swarm 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 |
|---|---|---|---|---|---|---|
| Qcsd Refinement Swarm this skillproffesor-for-testing/agentic-qe | 495 | — | ~1.5k | Automated safety check: Pass | MIT | |
| User Story Writerdeanpeters/Product-Manager-Skills | 7.2k | 2 repos | ~2.9k | Automated safety check: Pass | Custom licence | |
| Game Changing FeaturesopenstatusHQ/data-table-filters | 2.3k | 3 repos | ~2.1k | Automated safety check: Pass | MIT | |
| CCPM Project Managementautomazeio/ccpm | 8.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Convex Create Componentspokvulcan/poker-planning | 114 | 8 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Self Improving Agentfarm-fe/farm | 5.6k | 2 repos | ~3.3k | Automated safety check: Notes | MIT |
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Game Changing Features
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CCPM Project Management
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Runs a spec-driven workflow from PRD to epic to GitHub issues to parallel agents, with status, standup and blocked-work reports from bundled scripts.
Convex Create Component
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Builds reusable Convex components with isolated tables and app-facing APIs.
Self Improving Agent
farm-fe/farm
A universal self-improving agent that learns from ALL skill experiences.
Weekly Engineering Retro
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Builds a weekly engineering retrospective from git history: commit counts, per-person contributions, work patterns and code quality numbers over a chosen window.
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Categories
Questions about Qcsd Refinement Swarm
What does Qcsd Refinement Swarm do?
A skill your agent uses when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase. Qcsd Refinement Swarm is an agent skill from proffesor-for-testing/agentic-qe. Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
When should I use Qcsd Refinement Swarm?
Qcsd Refinement Swarm fits situations like: running Sprint Refinement sessions with SFDIPOT product factors; generating BDD scenarios; validating requirements in the QCSD Refinement phase.
How do I install Qcsd Refinement Swarm in Claude Code?
Run `npx skills add proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a claude-code`. Or copy the skill folder (assets/skills/qcsd-refinement-swarm in proffesor-for-testing/agentic-qe) into .claude/skills/qcsd-refinement-swarm in your project. Claude Code loads it when a task matches its description.
How do I install Qcsd Refinement Swarm in Codex?
Run `npx skills add proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a codex`. Or copy the skill folder (assets/skills/qcsd-refinement-swarm in proffesor-for-testing/agentic-qe) into .agents/skills/qcsd-refinement-swarm in your project. Codex loads it when a task matches its description.
Can I use Qcsd Refinement Swarm 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 proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qcsd-refinement-swarm, .gemini/skills/qcsd-refinement-swarm, .github/skills/qcsd-refinement-swarm and .opencode/skills/qcsd-refinement-swarm in your project.
What does Qcsd Refinement Swarm need to run?
SKILL.md names no scripts, command-line tools or credentials: Qcsd Refinement Swarm is instructions for the agent only.
Does Qcsd Refinement Swarm 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 Qcsd Refinement Swarm 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Qcsd Refinement Swarm use?
Qcsd Refinement Swarm is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Qcsd Refinement Swarm use?
About 1.5k tokens (SKILL.md is roughly 5.8k 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 Qcsd Refinement Swarm?
Skills that share tags, products or a category with Qcsd Refinement Swarm: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars), CCPM Project Management (automazeio/ccpm, 8.4k stars) and Convex Create Component (spokvulcan/poker-planning, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Qcsd Refinement Swarm?
proffesor-for-testing (a GitHub user) maintains it in proffesor-for-testing/agentic-qe, which has 495 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 4, 2026.
Source: proffesor-for-testing/agentic-qe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.