Agentic Atlas

Field-tested patterns for designing agent systems

Agentic Atlas helps you design and review agent systems: skills, subagents, plugins, hooks, and multi-agent workflows. Connect it, then ask your AI a design question in plain language.

What you can ask

Review my agent skill against Agentic Atlas patterns.
Example path

MCP connector

Server URL: https://agentic-atlas.dev/mcp/
Login: None
Protocol: MCP 2026-07-28 · Skills · Interactive UI
Instructions: Consult one active Agentic Atlas Release. Every tool addresses its payload directly: call with the canonical ids you already know, for any exact canonical address, and only when you do not yet have an identity. Node discovery keeps its leading lexical matches and adds neighbors sharing query terms through inbound and outbound references. A candidate's via identifies its seed, reference direction, and source Section; an absent via means a direct match. Judge every candidate against the task before requesting its Card; total counts the candidates. For a broad design or review, query each distinct concern and check for missing concepts as well as mechanisms. Empty listings, exact id/title lookups, Decisions, and terms do not expand. A complete Node from is prose alone; its relationships come from . Carry the coherence marker each payload returns as expected_revision on every later call, so a promotion is refused rather than silently crossed. Use for the canonical tree or the publisher-curated tour. Every payload's scope.omitted_fact_classes names what it withheld; each class has one fixed recovery: claims via , sections via , and links via , each addressed at the subject in hand; provenance via with the subject id and provenance=true; decisions via with query='' and kind='decision', then a single decision via at the returned 'decision:<decision-id>' address; terms via with kind='term', then optionally at the returned 'term:<key>' address. A definition read names that term: subject and declares no omitted fact classes. A truncated collection returns scope.next_cursor; continue it by repeating the same call with cursor.

Tools

Reads data5

Skills

3 in the ChatGPT listing

MCP connector

Server URL

https://agentic-atlas.dev/mcp/

None

Protocol

MCP 2026-07-28 · Skills · Interactive UI

Instructions

Consult one active Agentic Atlas Release. Every tool addresses its payload directly: call with the canonical ids you already know, for any exact canonical address, and only when you do not yet have an identity. Node discovery keeps its leading lexical matches and adds neighbors sharing query terms through inbound and outbound references. A candidate's via identifies its seed, reference direction, and source Section; an absent via means a direct match. Judge every candidate against the task before requesting its Card; total counts the candidates. For a broad design or review, query each distinct concern and check for missing concepts as well as mechanisms. Empty listings, exact id/title lookups, Decisions, and terms do not expand. A complete Node from is prose alone; its relationships come from . Carry the coherence marker each payload returns as expected_revision on every later call, so a promotion is refused rather than silently crossed. Use for the canonical tree or the publisher-curated tour. Every payload's scope.omitted_fact_classes names what it withheld; each class has one fixed recovery: claims via , sections via , and links via , each addressed at the subject in hand; provenance via with the subject id and provenance=true; decisions via with query='' and kind='decision', then a single decision via at the returned 'decision:<decision-id>' address; terms via with kind='term', then optionally at the returned 'term:<key>' address. A definition read names that term: subject and declares no omitted fact classes. A truncated collection returns scope.next_cursor; continue it by repeating the same call with cursor.

Skills

3 in the ChatGPT listing