How does a parent agent prove what a child did, received, and returned?
Find parent IDs, child IDs, sent payloads, received results, lifecycle states, cancellation behavior, and merge rules.
A project appears here because the boundary is relevant to its documented or reported architecture. The evidence label says how far this Atlas has checked the mechanism.
The runtime can inspect pending input, resolve permissions and tool mode, run hooks, and add higher-authority context before a model invocation is assembled.
BeforeAgent and related hook boundaries let the runtime attach delimited context or block a run before the next agent step.
Thread-local approval state narrows the risk that consent for one task becomes ambient authority for another.
Diff evidence becomes trustworthy only when the runtime records enough repository state to distinguish agent output from a guessed comparison.
An adapter can turn a public API description into model-visible tools while keeping schema validation, credentials, execution, and result handling separate.
A retained run keeps changes beside the working tree until a reviewer selects, applies, releases, or discards the output once.
The project documents an automation mode in which permission prompts are disabled, making the trust placed in the surrounding CI or sandbox environment explicit.
The documented daemon mode serves one agent session to multiple clients over HTTP and server-sent events, turning client identity and session ownership into protocol questions.
The project documents human-in-the-loop suspension backed by storage so a workflow can pause and later resume from durable execution state.
The project documents a Plan mode for investigation and strategy, an Act mode for execution, per-action approvals, optional auto-approval, diffs, and reversible checkpoints.
The framework presents agent dependencies, tool inputs, and structured results through Python types and validation boundaries.
The repository separates agent construction from explicit multi-agent workflow and deployment APIs in two language ecosystems.
The same control surface can connect to an agent running directly on a host, in Docker, on a VM, or in a cloud service; the README explicitly warns that an unsandboxed server has full filesystem access.
Crew and task abstractions make responsibilities explicit, but dependable delegation also requires lifecycle, authority, result, cancellation, and evidence semantics.
A direct message resolves to a personal scope, a group message to a group scope, and a channel to a channel scope; the resolver then mounts organization state read-only and the active scope read-write before a harness runs.
The launch command configures distinct protocol, context, compaction, state, and permission adapters for Claude Code, Codex, OpenCode, OpenClaw, Hermes, and Pi instead of treating one compatible endpoint as complete agent equivalence.
A BEHAVIOR.md names recurring expected conduct and its failure boundary; prompts, skills, traces, rubrics, and scorers can change around it without silently becoming the source of truth.
The monolith writes a future wake epoch, the always-alive dispatcher turns it into a trajectory step, and a backoff policy decides how soon the agent should think again based on whether the last wake produced visible work, only a thought, an idle, or an error.
The bundled code, dependency, and cloud-posture workflows name concrete scanners, require coverage disclosures when a tool is missing, and reserve fixes or cloud changes for reviewable code paths.
Structured send and receive logs make subagent work traceable. openai/codex
Builder Work: 143 Turns Coding Agents Into Team InfrastructureA builder project routes agents through durable sessions, sandboxes, previews, and PRs. assembledhq/143
Agent Events Are Getting Return AddressesReturn addresses explain why event identity matters before delegation scales. openai/codex, openclaw/openclaw, charmbracelet/crush, NousResearch/hermes-agent
October 19, 2026 — New request observers expose outcomes and available token usage. Where you put them in the sequence changes when a tool can leave the queue. openai/codex
Unsloth Can Reject a New Model to Keep Another LoadedOctober 19, 2026 — New Studio code gives chat, image and video models a choice: share GPU memory when possible, make room, or refuse a disruptive load. When media does displace chat, it can also save the primary GGUF model’s cached work. unslothai/unsloth
How Codex made the assignment the center of the appOctober 16, 2026 — Every’s origin story celebrates a desktop built around agents. The public record reveals the quieter achievement underneath: separating the machinery that does the work from the interface that helps people direct it. openai/codex
Gemini CLI Now Sends Gemini 4 Users to AntigravityOctober 16, 2026 — Google’s open-source terminal agent now warns that it is not optimized for Gemini 4 Argon. The recommendation makes its direction clearer while fresh implementation fixes show a project still being maintained. google-gemini/gemini-cli, google-antigravity/antigravity-cli
QM Drops Two Agent Loops but Keeps ChatGPT AccessOctober 15, 2026 — The shared workplace agent is narrowing its runtime choices to Pi and Claude. Its October 14 code change shows why keeping a model connection does not require keeping the agent software that shares its name. yc-software/qm, different-ai/openwork
Gemini’s Longer Answers Now Span Multiple RequestsOctober 14, 2026 — Google’s Argon can continue a response beyond one request’s output limit. Pydantic AI’s released integration shows what that means for an agent: one answer, several network calls, and two different ways of counting tokens. pydantic/pydantic-ai
Hermes Puts Assembled Agent Instructions into Code ReviewOctober 12, 2026 — A new snapshot shows reviewers the system prompt and tool definitions produced by the code. Nine controlled configurations turn changes in the agent’s instructions into something maintainers can compare directly. NousResearch/hermes-agent
Unsloth Adds Shared Fine-Tuning for Seven Text-Diffusion FamiliesOctober 11, 2026 — A new trainer connects familiar datasets to distinct learning recipes for models that refine text instead of only predicting the next token. The gain is less custom integration—and a clearer view of the differences that still matter. unslothai/unsloth
This is a mechanism comparison, not a feature score. “Reporting underway” means the Atlas has not verified the relevant path; it does not mean the project lacks it.