OpenLogi macOS Permissions Triage
AprilNEA/OpenLogi
Decides whether an OpenLogi device problem on macOS is a privacy-permission (TCC) problem, using agent log lines, and says which identity needs which grant.
A skill your agent uses when assessing post-release production health with DORA metrics, root cause analysis, defect prediction, or cross-phase feedback loops in the QCSD Production phase.
Install Qcsd Production Swarm
$ npx skills add proffesor-for-testing/agentic-qe --skill qcsd-production-swarm -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-production-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-production-swarm .claude/skills/qcsd-production-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-production-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-production-swarm into .claude/skills/qcsd-production-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-production-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-production-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-production-swarm -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-production-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-production-swarm .agents/skills/qcsd-production-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-production-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-production-swarm into .agents/skills/qcsd-production-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-production-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-production-swarm -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-production-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-production-swarm .cursor/skills/qcsd-production-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-production-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-production-swarm into .cursor/skills/qcsd-production-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-production-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-production-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-production-swarm -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install proffesor-for-testing/agentic-qe qcsd-production-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-production-swarm .gemini/skills/qcsd-production-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-production-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-production-swarm into .gemini/skills/qcsd-production-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-production-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-production-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-production-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-production-swarm .github/skills/qcsd-production-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-production-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-production-swarm into .github/skills/qcsd-production-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-production-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-production-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-production-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-production-swarm .opencode/skills/qcsd-production-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-production-swarm" agent skill from https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/qcsd-production-swarm into .opencode/skills/qcsd-production-swarm/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qcsd-production-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-production-swarm- GitHub stars
- 495
- Token cost
- ~2.3k tokens
- SKILL.md length
- 726 words
- Files
- 13 (incl. scripts)
- Skills in repo
- 93
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when assessing post-release production health with DORA metrics, root cause analysis, defect prediction, or cross-phase feedback loops in the QCSD Production phase.
- Works in 9 steps: Flag Detection --… → Core Agents -- steps/02-core-agents.md… → Batch 1 Results --… → …
- Assessing post-release production health with DORA metrics
- SKILL.md covers Overview, ENFORCEMENT RULES - READ FIRST, Step Execution Protocol and Agent Inventory, plus 4 more sections
- Root cause analysis
What it does
Qcsd Production Swarm is an agent skill from proffesor-for-testing/agentic-qe. Use when assessing post-release production health with DORA metrics, root cause analysis, defect prediction, or cross-phase feedback loops in the QCSD Production phase.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts (for example `evals/qcsd-production-swarm.yaml`, `schemas/output.json` and `scripts/validate-config.json`).
It sits in Development, covering Root cause analysis. 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
- Assessing post-release production health with DORA metrics
- Root cause analysis
- Defect prediction
- Cross-phase feedback loops in the QCSD Production phase
Example prompts
- “/qcsd-production-swarm”
Workflow steps
9 steps, taken from the first numbered list in SKILL.md.
- Flag Detection -- steps/01-flag-detection.md -- Retrieve CI/CD signals, detect telemetry source, evaluate all 7 flags
- Core Agents -- steps/02-core-agents.md -- Spawn qe-metrics-optimizer, qe-defect-predictor, qe-root-cause-analyzer in parallel
- Batch 1 Results -- steps/03-batch1-results.md -- Wait for core agents, extract all metrics
- Conditional Agents -- steps/04-conditional-agents.md -- Spawn flagged conditional agents in parallel
- Decision Synthesis -- steps/05-decision-synthesis.md -- Apply HEALTHY/DEGRADED/CRITICAL logic
- Report Generation -- steps/06-report-generation.md -- Generate executive summary and full report
- Learning Persistence -- steps/07-learning-persistence.md -- Store findings to memory, save persistence record
- Feedback Loop -- steps/08-feedback-loop.md -- Run learning coordinator then transfer specialist (sequential)
- Final Output -- steps/09-final-output.md -- Display completion summary with all scores
What it can do on your machine
Read from SKILL.md and the folder at commit 1363bc7. 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 Production Swarm loads about 2.3k tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 726 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 1363bc7, republished under its MIT licence (© proffesor-for-testing). 726 words, ~2,281 tokens.
Download SKILL.mdSave it as
.claude/skills/qcsd-production-swarm/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.- name
- qcsd-production-swarm
- description
- Use when assessing post-release production health with DORA metrics, root cause analysis, defect prediction, or cross-phase feedback loops in the QCSD Production phase.
- category
- qcsd-phases
- priority
- critical
- version
- 1.0.0
- tokenEstimate
- 32000
- agents.core
- qe-metrics-optimizer, qe-defect-predictor, qe-root-cause-analyzer
- agents.conditional
- qe-chaos-engineer, qe-performance-tester, qe-regression-analyzer, qe-pattern-learner, qe-middleware-validator, qe-sap-rfc-tester, qe-sod-analyzer
- agents.feedback
- qe-learning-coordinator, qe-transfer-specialist
- agents.total
- 12
- agents.sub_agents
- 0
- skills
- shift-right-testing, chaos-engineering-resilience, quality-metrics, performance-testing, holistic-testing-pact
QCSD Production Swarm v1.0
Post-release production health assessment and QCSD feedback loop closure.
Overview
The Production Swarm assesses release health in the live production environment using DORA metrics, incident RCA, defect prediction, and cross-phase feedback loops. It renders a HEALTHY / DEGRADED / CRITICAL decision and is the only QCSD phase with dual responsibility: assessing current production health AND closing the feedback loop back to Ideation and Refinement phases.
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
TELEMETRY_DATA: Path to production telemetry, incident reports, and DORA metrics (required)RELEASE_ID: Release identifier for tracking (optional)OUTPUT_FOLDER: Where to save reports (default:${PROJECT_ROOT}/Agentic QCSD/production/)SLA_DEFINITIONS: Path to SLA/SLO target definitions (optional)
ENFORCEMENT RULES - READ FIRST
| Rule | Enforcement |
|---|---|
| E1 | You MUST spawn ALL THREE core agents in Step 2. No exceptions. |
| E2 | You MUST put all parallel Task calls in a SINGLE message. |
| E3 | You MUST STOP and WAIT after each batch. No proceeding early. |
| E4 | You MUST spawn conditional agents if flags are TRUE. No skipping. |
| E5 | You MUST apply HEALTHY/DEGRADED/CRITICAL logic exactly as specified in Step 5. |
| E6 | You MUST generate the full report structure. No abbreviated versions. |
| E7 | Each agent MUST read its reference files before analysis. |
| E8 | You MUST run BOTH feedback agents in Step 8 SEQUENTIALLY. Always. Both agents. |
| E9 | You MUST execute Step 7 learning persistence. No skipping. |
PROHIBITED BEHAVIORS:
- Summarizing instead of spawning agents
- Skipping agents "for brevity"
- Proceeding before background tasks complete
- Providing your own analysis instead of spawning specialists
- Omitting report sections or using placeholder text
Step Execution Protocol
This skill uses a micro-file step architecture. Each step is a self-contained file loaded one at a time to avoid "lost in the middle" context degradation.
Execute steps sequentially by reading each step file with the Read tool.
Steps
- Flag Detection --
steps/01-flag-detection.md-- Retrieve CI/CD signals, detect telemetry source, evaluate all 7 flags - Core Agents --
steps/02-core-agents.md-- Spawn qe-metrics-optimizer, qe-defect-predictor, qe-root-cause-analyzer in parallel - Batch 1 Results --
steps/03-batch1-results.md-- Wait for core agents, extract all metrics - Conditional Agents --
steps/04-conditional-agents.md-- Spawn flagged conditional agents in parallel - Decision Synthesis --
steps/05-decision-synthesis.md-- Apply HEALTHY/DEGRADED/CRITICAL logic - Report Generation --
steps/06-report-generation.md-- Generate executive summary and full report - Learning Persistence --
steps/07-learning-persistence.md-- Store findings to memory, save persistence record - Feedback Loop --
steps/08-feedback-loop.md-- Run learning coordinator then transfer specialist (sequential) - Final Output --
steps/09-final-output.md-- Display completion summary with all scores
Show full SKILL.md (305 more words)Show less
Execution Instructions
- Use the Read tool to load the current step file (e.g.,
Read({ file_path: ".claude/skills/qcsd-production-swarm/steps/01-flag-detection.md" })) - Execute the step's instructions completely
- Verify all success criteria are met before proceeding
- Pass the step's output as context to the next step
- If a step fails, halt and report the failure point -- do not skip ahead
Resume Support
To resume from a specific step: specify --from-step N and the orchestrator will
skip to step N. Ensure you have the required prerequisite data from prior steps.
Agent Inventory
| Agent | Type | Domain | Batch |
|---|---|---|---|
| qe-metrics-optimizer | Core (always) | learning-optimization | 1 |
| qe-defect-predictor | Core (always) | defect-intelligence | 1 |
| qe-root-cause-analyzer | Core (always) | defect-intelligence | 1 |
| qe-chaos-engineer | Conditional (HAS_INFRASTRUCTURE_CHANGE) | chaos-resilience | 2 |
| qe-performance-tester | Conditional (HAS_PERFORMANCE_SLA) | chaos-resilience | 2 |
| qe-regression-analyzer | Conditional (HAS_REGRESSION_RISK) | defect-intelligence | 2 |
| qe-pattern-learner | Conditional (HAS_RECURRING_INCIDENTS) | defect-intelligence | 2 |
| qe-middleware-validator | Conditional (HAS_MIDDLEWARE) | enterprise-integration | 2 |
| qe-sap-rfc-tester | Conditional (HAS_SAP_INTEGRATION) | enterprise-integration | 2 |
| qe-sod-analyzer | Conditional (HAS_AUTHORIZATION) | enterprise-integration | 2 |
| qe-learning-coordinator | Feedback (always, sequential) | learning-optimization | 3 |
| qe-transfer-specialist | Feedback (always, sequential) | learning-optimization | 3 |
Total: 12 agents (3 core + 7 conditional + 2 feedback)
Quality Gate Thresholds
| Metric | HEALTHY | DEGRADED | CRITICAL |
|---|---|---|---|
| DORA Score | >= 0.7 | 0.4 - 0.69 | < 0.4 |
| SLA Compliance | >= 99% | 95 - 98.9% | < 95% |
| Incident Severity | P3/P4/NONE | P2 | P0/P1 |
| Defect Trend | declining/stable | stable (density > 2) | increasing + density > 5 |
| RCA Completeness | >= 80% | 50 - 79% | < 50% |
Report Filename Mapping
| Agent | Report Filename | Step |
|---|---|---|
| qe-metrics-optimizer | 02-dora-metrics.md | 2 |
| qe-defect-predictor | 03-defect-prediction.md | 2 |
| qe-root-cause-analyzer | 04-root-cause-analysis.md | 2 |
| qe-chaos-engineer | 05-chaos-resilience.md | 4 |
| qe-performance-tester | 06-performance-sla.md | 4 |
| qe-regression-analyzer | 07-regression-analysis.md | 4 |
| qe-pattern-learner | 08-pattern-analysis.md | 4 |
| Learning Persistence | 09-learning-persistence.json | 7 |
| qe-middleware-validator | 10-middleware-health.md | 4 |
| qe-sap-rfc-tester | 11-sap-health.md | 4 |
| qe-sod-analyzer | 12-sod-compliance.md | 4 |
| Feedback agents | 13-feedback-loops.md | 8 |
| Synthesis | 01-executive-summary.md | 6 |
Execution Model Options
| Model | When to Use | Agent Spawn |
|---|---|---|
| Task Tool (PRIMARY) | Claude Code sessions | Task({ subagent_type, run_in_background: true }) |
| MCP Tools | MCP server available | fleet_init({}) / task_submit({}) |
| CLI | Terminal/scripts | swarm init / agent spawn |
Key Principle
Production health is measured by outcomes, not intentions. This swarm provides evidence-based production assessment and closes the QCSD feedback loop.
© 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-production-swarm of proffesor-for-testing/agentic-qe.
- SKILL.md
- evals/qcsd-production-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-feedback-loop.md
- steps/09-final-output.md
Open the folder on GitHubat commit 1363bc7
Compare with similar skills
Qcsd Production 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 Production Swarm this skillproffesor-for-testing/agentic-qe | 495 | — | ~2.3k | Automated safety check: Pass | MIT | |
| OpenLogi macOS Permissions TriageAprilNEA/OpenLogi | 23k | — | ~2.5k | Automated safety check: Notes | Apache-2.0 | |
| Bug Finder for daisyUIsaadeghi/daisyui | 43k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Root Cause Debugginggarrytan/gstack | 136k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Review PRapache/shardingsphere | 21k | — | ~6.5k | Automated safety check: Pass | Apache-2.0 | |
| Graph-Based Bug Tracingtirth8205/code-review-graph | 32k | 1 repos | ~287 | Automated safety check: Pass | MIT |
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Questions about Qcsd Production Swarm
What does Qcsd Production Swarm do?
A skill your agent uses when assessing post-release production health with DORA metrics, root cause analysis, defect prediction, or cross-phase feedback loops in the QCSD Production phase. Qcsd Production Swarm is an agent skill from proffesor-for-testing/agentic-qe. Use when assessing post-release production health with DORA metrics, root cause analysis, defect prediction, or cross-phase feedback loops in the QCSD Production phase.
When should I use Qcsd Production Swarm?
Qcsd Production Swarm fits situations like: assessing post-release production health with DORA metrics; root cause analysis; defect prediction; cross-phase feedback loops in the QCSD Production phase.
How do I install Qcsd Production Swarm in Claude Code?
Run `npx skills add proffesor-for-testing/agentic-qe --skill qcsd-production-swarm -a claude-code`. Or copy the skill folder (assets/skills/qcsd-production-swarm in proffesor-for-testing/agentic-qe) into .claude/skills/qcsd-production-swarm in your project. Claude Code loads it when a task matches its description.
How do I install Qcsd Production Swarm in Codex?
Run `npx skills add proffesor-for-testing/agentic-qe --skill qcsd-production-swarm -a codex`. Or copy the skill folder (assets/skills/qcsd-production-swarm in proffesor-for-testing/agentic-qe) into .agents/skills/qcsd-production-swarm in your project. Codex loads it when a task matches its description.
Can I use Qcsd Production 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-production-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-production-swarm, .gemini/skills/qcsd-production-swarm, .github/skills/qcsd-production-swarm and .opencode/skills/qcsd-production-swarm in your project.
What does Qcsd Production Swarm need to run?
SKILL.md names no scripts, command-line tools or credentials: Qcsd Production Swarm is instructions for the agent only.
Does Qcsd Production 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 Production 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 Production Swarm use?
Qcsd Production 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 Production Swarm use?
About 2.3k tokens (SKILL.md is roughly 9.1k 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 Production Swarm?
Skills that share tags, products or a category with Qcsd Production Swarm: OpenLogi macOS Permissions Triage (AprilNEA/OpenLogi, 23k stars), Bug Finder for daisyUI (saadeghi/daisyui, 43k stars), Root Cause Debugging (garrytan/gstack, 136k stars) and Review PR (apache/shardingsphere, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Qcsd Production 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 9, 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.