Global Chat Agent Discovery workflow skill. Use this skill when the user needs Discover and search 18K+ MCP servers and AI agents across 6+ registries using Global Chat's cross-protocol directory and MCP server and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
Global Chat Agent Discovery workflow skill. Use this skill when the user needs Discover and search 18K+ MCP servers and AI agents across 6+ registries using Global Chat's cross-protocol directory and MCP server and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/global-chat-agent-discovery from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
Global Chat Agent Discovery
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Common Pitfalls, Limitations.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
Use when you need to find an MCP server for a specific capability (e.g., database access, file conversion, API integration)
Use when evaluating which agent registries carry tools for your use case
Use when you want to search across multiple protocols (MCP, A2A, agents.txt) simultaneously
Use when setting up agent-to-agent communication and need to discover available endpoints
Use when the request clearly matches the imported source intent: Discover and search 18K+ MCP servers and AI agents across 6+ registries using Global Chat's cross-protocol directory and MCP server.
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
Validate the result against the upstream expectations and the evidence you can point to in the copied files.
Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.
Imported Workflow Notes
Imported: Overview
Global Chat is a cross-protocol AI agent discovery platform that aggregates MCP servers and AI agents from 6+ registries into a single searchable directory. This skill helps you find the right MCP server, A2A agent, or agents.txt endpoint for any task by searching across 18,000+ indexed entries. It also provides an MCP server (@global-chat/mcp-server) for programmatic access to the directory from any MCP-compatible client.
Imported: How It Works
Option 1: Use the MCP Server (Recommended for Agents)
Install the Global Chat MCP server to search the directory programmatically from Claude Code, Cursor, or any MCP client.
Enter your domain or paste your agents.txt content
Get instant feedback on format compliance and discoverability
Examples
Example 1: Ask for the upstream workflow directly
Use @global-chat-agent-discovery to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @global-chat-agent-discovery against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @global-chat-agent-discovery for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @global-chat-agent-discovery using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Imported Usage Notes
Imported: Examples
Example 1: Find MCP Servers for a Task
You: "Find MCP servers that can convert PDF files to text"
Agent (via Global Chat MCP): Searching across 6 registries...
- @anthropic/pdf-tools (mcpservers.org) — PDF parsing and text extraction
- pdf-converter-mcp (mcp.so) — Convert PDF to text, markdown, or HTML
- ...
Example 2: Discover A2A Agents
You: "What A2A agents are available for code review?"
Agent (via Global Chat MCP): Found 12 A2A agents for code review across 3 registries...
Example 3: Check Agent Protocol Coverage
You: "How many registries list tools for Kubernetes management?"
Agent (via Global Chat MCP): 4 registries carry Kubernetes-related agents (23 total entries)...
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Use the MCP server for automated workflows and agent-to-agent discovery
Use the web directory for manual exploration and comparison
Validate your agents.txt before publishing to ensure maximum discoverability
Check multiple registries — coverage varies significantly by domain
Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
Imported Operating Notes
Imported: Best Practices
Use the MCP server for automated workflows and agent-to-agent discovery
Use the web directory for manual exploration and comparison
Validate your agents.txt before publishing to ensure maximum discoverability
Check multiple registries — coverage varies significantly by domain
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/global-chat-agent-discovery, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a
Imported Reference Notes
Imported: Common Pitfalls
Problem: Search returns too many results
Solution: Add protocol or registry filters to narrow the scope
Problem: MCP server not connecting
Solution: Ensure npx is available and run npx -y @global-chat/mcp-server manually first to verify
Imported: Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
