Leyline
Sorcery
Deep Agents (langchain-ai/deepagents) is LangChain AI’s batteries-included agent harness: production-ready, extensible, with filesystem, context management, sub-agent delegation, skills, and long-term memory (PyPI summary). README principles: opinionated, extensible, model-agnostic, production-ready on LangGraph + LangSmith.
[ Observed sample ]
The count is distinct observed stacks. It is not a Score input.
This component is not in Leyline's observed sample.
Record cmp_deep-agents
[ Score explain ]
Score v2 uses only observed signals. The displayed contribution is weight × value × 100. Missing factors are insufficient evidence.
Score factor
GitHub health18% weight. A licence is declared. Documentation is available.
Value 0.30 · 5.4 points
18% weight × 0.30 value
A licence is declared. Documentation is available.
Score factor
Agent use16% weight. insufficient evidence
insufficient evidence
insufficient evidence
insufficient evidence
Score factor
Human notes14% weight. insufficient evidence
insufficient evidence
insufficient evidence
insufficient evidence
Score factor
Composability16% weight. insufficient evidence
insufficient evidence
insufficient evidence
insufficient evidence
Score factor
Checklist10% weight. No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.
Value 0.00 · 0.0 points
10% weight × 0.00 value
No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.
Score factor
Evidence quality14% weight. 1 sources cover 1 evidence types. The latest dated evidence is 2026-09-09. Freshness is omitted unless observed as a signal.
Value 0.18 · 2.5 points
14% weight × 0.18 value
1 sources cover 1 evidence types. The latest dated evidence is 2026-09-09. Freshness is omitted unless observed as a signal.
Score factor
Benchmarks12% weight. insufficient evidence
insufficient evidence
insufficient evidence
insufficient evidence
Agent use: insufficient evidence
Human notes: insufficient evidence
Composability: insufficient evidence
Benchmarks: insufficient evidence
[ Claims ]
Claims are what the publisher declares. Score uses observed signals, not these assertions, except for checklist fields derived from interfaces. MCP, API, cost, and license claims are marked verified, unverified, or contradicted from intake evidence.
audience
AgentsThe product is built for software agents to call, not only for interactive humans.
Agents Browse Agents[ Capability slices ]
Deep Agents (langchain-ai/deepagents) is LangChain AI’s batteries-included agent harness: production-ready, extensible, with filesystem, context management, sub-agent delegation, skills, and long-term memory (PyPI summary). README principles: opinionated, extensible, model-agnostic, production-ready on LangGraph + LangSmith.
Deep Agents (langchain-ai/deepagents) is LangChain AI’s batteries-included agent harness: production-ready, extensible, with filesystem, context management, sub-agent delegation, skills, and long-term memory (PyPI summary). README principles: opinionated, extensible, model-agnostic, production-ready on LangGraph + LangSmith.
[ Relations ]
[ Signals ]
Signals carry source, method, and observedAt. Source review dates and evidence basis are shown separately. Unobserved metrics stay insufficient evidence.
Evidence basis unknown · Check date unknown · Source date 2026-09-09
No social source is stored.
Propose a change with a public source. Corrections wait for review before the card changes.
[ Notes ]
No notes are stored.