Install
$ agentstack add skill-jonatangs777-ai-skill-agent-control-deck-2026-automation-agentic-workflow-automation-skill-2026 ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Automation Agentic Workflow Automation Skill 2026 Skill
Mission
Disena procesos automatizados para agentic workflow automation con control logico, trazabilidad completa y validacion operativa de extremo a extremo.
When to use
- When the user asks for a repeatable workflow in this domain.
- When a specialized checklist improves speed or quality.
Inputs expected
- Task objective and expected output.
- Relevant files, paths, or system constraints.
- Any non-negotiable requirements (security, style, deadlines).
Workflow
- Understand scope, assumptions, and risks.
- Execute the workflow in a deterministic order.
- Verify outcomes and report any limitations clearly.
Output contract
Provide results in this order: key outcome, concrete changes, validation status, next steps.
Guardrails
- Never fabricate facts, outputs, or tool results.
- Ask for confirmation before destructive operations.
- Prefer minimal, reversible changes when uncertain.
Foundations
logic-of-programs-hoarealgorithm-correctness-invariantsdistributed-systems-consistency-foundationstesting-verification-foundationssecurity-threat-modeling-foundationsdebugging-causal-reasoning-foundations
Logical reliability checklist
- Assumptions are explicit and separated from verified facts.
- The solution path is justified with clear reasoning steps.
- Edge cases and contradiction checks are included.
- Output is testable, auditable, and reversible when possible.
Example prompts
- "Apply the automation-agentic-workflow-automation-skill-2026 skill to handle this task end-to-end."
- "Run automation-agentic-workflow-automation-skill-2026 and produce a production-ready output with validation notes."
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: JonatanGS777
- Source: JonatanGS777/ai-skill-agent-control-deck-2026
- License: MIT
- Homepage: https://github.com/JonatanGS777/ai-skill-agent-control-deck-2026
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.