Daily AI Implementation Scout Council

Today's ranked top 20

#1

build nowClaude (Axion)32 / 35

Claude Agent SDK for Python repo

Anthropic's official Python library that exposes the Claude Code agent loop, built in tools, and context management as an embeddable SDK, currently at release v0.2.152.

What it does for you: Lets YY run the same agent loop that powers Claude Code inside custom Python scripts or servers, so a Hermes style runtime can spawn subagents, hooks, and permission logic without reimplementing the harness from scratch. The latest release adds a defer hook decision, strict MCP config options, and updatedToolOutput for post tool hooks, all of which reduce custom glue code the Telegram bridge would otherwise need to write by hand.

In practice: This is the actual plumbing under Axion, worth tracking release notes on weekly rather than treating as optional reading.

For: Claude (Axion). This is Anthropic's own SDK for embedding the Claude Code agent loop in custom software, so it is Claude specific by definition and is what a Hermes style runtime would be built on top of.

Security5

Quality4

Auditability4

Useful to you5

Useful to community4

Buildable now5

Hermes5

Verdict: build now. Score 32. Axion's Telegram bridge and any future Hermes runtime already depend on this SDK's stability, and the new hook features are usable immediately without a design decision first.

Build #1 Claude Agent SDK for Python: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/anthropics/claude-agent-sdk-python. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · GitHub shows 8,000 stars and 1,300 forks as of 2026-09-03. Latest release is v0.2.152, published to PyPI, bundling Claude CLI 2.1.259, confirmed on the repo Releases page.

#2

newtest firstBoth runtimes28 / 35

sandbox-runtime repo

An open source OS level sandboxing tool from Anthropic that restricts filesystem and network access for arbitrary processes without requiring a container, the same isolation code used inside Claude Code's own bash sandbox.

What it does for you: Lets YY wrap Axion's agent generated shell commands, local MCP servers, or any untrusted subprocess in filesystem and network restrictions on his own machine, using native primitives, sandbox-exec on macOS and bubblewrap on Linux, plus a network proxy filter, so no Docker install is needed. It is the closest thing to a ready made permission fence for exactly the kind of agent driven shell commands Axion already runs.

In practice: The most directly relevant and credible pick in this lens because it is literally Anthropic hardening its own Claude Code sandbox and open sourcing it.

For: Both runtimes. OS level sandboxing wraps any subprocess Axion or a Hermes runtime spawns, on macOS or Linux, so it is not tied to one specific agent runtime.

Security3

Quality4

Auditability4

Useful to you5

Useful to community3

Buildable now4

Hermes5

Verdict: test first. Score 28. High relevance to Axion's own bash and MCP execution, but a known network sandbox escape advisory means it needs a supervised trial before being trusted for anything sensitive.

Build #2 sandbox-runtime: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/anthropics/sandbox-runtime. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 4,800 GitHub stars and latest release v0.0.68 dated 2026-07-24, per the repo releases page. A published security advisory GHSA-9gqj-5w7c-vx47 describes a network sandboxing escape, and issue #88 documents a DNS resolution exfiltration path when allowLocalBinding is true.

#3

test firstBoth runtimes28 / 35

Langfuse repo

A self hostable open source LLM engineering platform combining tracing, prompt management, and evaluation including LLM as judge scoring, currently at release v4.28.1.

What it does for you: Self host it once and get a full trace viewer for every Axion agent and MCP call, prompt version history so a bad hook writer prompt edit can be rolled back, and built in LLM as judge scoring pointed at Hermes runs to catch quality regressions before YY sees them. It integrates with OpenTelemetry so it can sit under Claude Code's existing OTel hooks without custom glue code.

In practice: The most mature and actively shipped option in this lens, with daily commits and a real community behind it.

For: Both runtimes. Self hostable observability platform that ingests OpenTelemetry traces, so it works with any LLM stack Axion or Hermes calls, not only Claude Code.

Security3

Quality5

Auditability4

Useful to you4

Useful to community5

Buildable now3

Hermes4

Verdict: test first. Score 28. Most production grade of the observability options, but self hosting its ClickHouse backed data layer is real infrastructure that should be piloted before committing Axion's tracing backbone to it.

Build #3 Langfuse: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/langfuse/langfuse. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 34,163 GitHub stars, latest tagged release v4.28.1 published 2026-09-03, repo pushed the same day, pulled directly from the GitHub API on 2026-09-04.

#4

test firstBoth runtimes28 / 35

Mem0 repo

An open source memory layer that extracts, stores, and retrieves facts from agent conversations across sessions, with official Python and TypeScript SDKs.

What it does for you: Drops into a Claude Code agent or MCP server as a persistent fact store so an agent remembers preferences, past decisions, and project state across separate sessions instead of losing everything when the context window resets. It ships an official Anthropic SDK integration, so it can sit alongside Claude Code without a custom adapter, and two SDK releases shipped in the last week alone, so the API is actively moving.

In practice: The most mature and widely adopted memory option, feels like the safe default rather than the interesting new thing.

For: Both runtimes. Ships generic Python and TypeScript SDKs plus 21 framework integrations, so it works equally from a Claude Agent SDK script or a Hermes runtime.

Security3

Quality5

Auditability4

Useful to you4

Useful to community4

Buildable now4

Hermes4

Verdict: test first. Score 28. Mature enough to trust for a pilot integration into a Hermes style runtime, but the fact extraction LLM calls add cost and latency worth measuring before committing.

Build #4 Mem0: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/mem0ai/mem0. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 64,662 GitHub stars and 7,575 forks, Apache 2.0 license, latest Python SDK release v2.0.20 and Node SDK release ts-v3.1.8 both published 2026-09-02, checked directly via the GitHub REST API on 2026-09-04.

#5

test firstBoth runtimes27 / 35

DeepEval repo

An Apache 2.0, Pytest style Python framework for LLM and agent evaluation with more than 50 built in metrics including LLM as judge, trajectory, and tool use scoring.

What it does for you: Lets YY write eval cases as normal Python test functions and score agent trajectories with metrics like TaskCompletionMetric, plugging into LangChain, Pydantic AI, and CrewAI callback hooks so an Axion agent can fail CI when a prompt change breaks behavior. It ships a dedicated quickstart aimed at people who build with an AI coding assistant rather than write eval harnesses by hand, which fits how YY already works.

In practice: Feels the most code native and CI friendly of the evaluation tools, closest to writing normal unit tests.

For: Both runtimes. A Python testing library that runs as normal unit tests, usable from any codebase regardless of which agent runtime is under evaluation.

Security4

Quality4

Auditability4

Useful to you4

Useful to community4

Buildable now4

Hermes3

Verdict: test first. Score 27. Active, well starred, and Python native fits a Claude Code and MCP stack directly, but a recent breaking change to score direction means a small pilot before trusting it in a regression gate.

Build #5 DeepEval: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/confident-ai/deepeval. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 18,085 GitHub stars, latest release python-v4.2.0 published 2026-08-24, repo pushed 2026-09-03, Apache 2.0 license, pulled directly from the GitHub API on 2026-09-04.

#6

newtest firstBoth runtimes27 / 35

Chonkie repo

An open source Python and JavaScript text chunking library built for RAG ingestion pipelines, offering token, semantic, sentence, recursive, and late chunking strategies.

What it does for you: Drops into an Axion ingest step to split brain documents and reports into chunks before embedding, so YY does not have to hand roll splitting logic for every corpus. Its stated throughput and small package size mean it can run inline in the nightly brain ingest without adding real latency or a heavy dependency tree.

In practice: A small, fast, purpose built tool that looks like a genuine time saver for the boring first mile of any RAG pipeline.

For: Both runtimes. A small Python and JS library callable from any ingest script, with no dependency on a specific agent runtime.

Security4

Quality3

Auditability4

Useful to you4

Useful to community3

Buildable now5

Hermes4

Verdict: test first. Score 27. Fast and lightweight enough to trial directly in the nightly brain ingest without a big integration cost, but should be piloted on one brain corpus before wiring into all of them.

Build #6 Chonkie: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/chonkie-inc/chonkie. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · PyPI shows current release 1.7.0, GitHub topic listing shows the repo at roughly 4,700 stars with recent activity dated 2026-08-22.

#7

newtest firstBoth runtimes26 / 35

Snyk Agent Scan repo

A CLI security scanner from Snyk that auto discovers local AI agent configurations, MCP servers, and agent skills, then scans them for prompt injection, tool poisoning, and malicious skill payloads.

What it does for you: YY could point this at Axion's Skills folder and any locally configured MCP servers before syncing them into the runtime, catching tool poisoning, credential handling issues, or hardcoded secrets in a skill before it ever executes against his accounts. It is the closest thing to an antivirus scan for the exact kind of skill and MCP sprawl Axion already has, with over 710 skills to check.

In practice: Practical and directly usable today with almost no setup cost, worth a one time run against the Skills folder this week.

For: Both runtimes. A CLI scanner that reads local skill and MCP configuration files directly, independent of which runtime later executes them.

Security5

Quality4

Auditability3

Useful to you4

Useful to community3

Buildable now4

Hermes3

Verdict: test first. Score 26. Free CLI scan of an already large skill library is low risk and could surface real issues fast, but detection rules for skill level threats are new and unproven, so treat findings as leads, not verdicts.

Build #7 Snyk Agent Scan: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/snyk/agent-scan. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 1,900 GitHub stars, Apache 2.0 license, per the repo page. Snyk announced general availability of the broader Agent Security product on 2026-03-23, with Agent Scan in open preview and a listed latest release around 2026-05-09.

#8

test firstBoth runtimes25 / 35

RAGFlow repo

An open source, self hostable RAG engine combining deep document parsing, chunk inspection, and agent workflow building in one system, currently at release v0.27.0.

What it does for you: Provides a full ingest to answer pipeline, parsing messy PDFs and docs, chunking with visual inspection, then retrieving for an agent, that could sit under a Hermes runtime as the retrieval backend for report and brain search. It has a built in MCP dashboard so it can expose retrieval as MCP tools directly to Claude Code agents, and a May 2026 update cut retrieval latency by 50 to 100 percent per the project's own release notes.

In practice: The most complete, most starred, most actively shipped tool in this lens, but it wants to be the whole system rather than a component to drop into Axion.

For: Both runtimes. A self hosted RAG engine reachable over its own API and MCP dashboard, usable from Claude Code or any other client that speaks MCP.

Security3

Quality4

Auditability3

Useful to you4

Useful to community4

Buildable now3

Hermes4

Verdict: test first. Score 25. Star count and shipping cadence are real and the MCP dashboard is directly relevant, but a history of breaking upgrades means a pilot on a throwaway corpus first, not a straight swap into production brains.

Build #8 RAGFlow: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/infiniflow/ragflow. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · Roughly 89,380 GitHub stars as of 2026-08-26 per a star history tracker, up from 83,300 stars on 2026-06-21. Latest tagged release is v0.27.0.

#9

newtest firstBoth runtimes25 / 35

mcp-compressor plugin

An MCP server wrapper from Atlassian Labs, shipped in TypeScript, Python, and Rust, that reduces the tokens consumed by MCP tool definitions and responses.

What it does for you: Sits between a Claude Code MCP client and existing MCP servers, compressing verbose tool schemas and tool call outputs before they reach context. For a solo operator running several MCP servers inside Hermes, this directly shrinks the fixed token tax every session pays just to list available tools, leaving more room for actual work.

In practice: Feels like exactly the kind of quiet infrastructure fix a large org builds for itself and open sources almost as an afterthought, worth a cautious trial.

For: Both runtimes. A proxy that sits between any MCP client and existing MCP servers, so it benefits Claude Code sessions and any other MCP based runtime equally.

Security3

Quality3

Auditability4

Useful to you4

Useful to community3

Buildable now4

Hermes4

Verdict: test first. Score 25. Directly addresses the MCP tool schema bloat problem Axion will hit as more servers are added, but needs a real token count test before wiring into production.

Install: clone atlassian-labs/mcp-compressor and run it as a local proxy in front of one existing MCP server first, per its README setup docs. Review before enabling. Copy

Source · 118 GitHub stars, Apache 2.0 license, maintained by Atlassian Labs with an active CI badge and a versioned releases page, verified by visiting the repo directly on 2026-09-03.

#10

newtest firstClaude (Axion)24 / 35

prompt-caching (flightlesstux) plugin

An MCP plugin and Claude Code plugin that automatically places cache_control breakpoints, analyzes cacheability, and tracks real time cache savings for Claude Code sessions.

What it does for you: Installs as a Claude Code plugin that watches repeated file reads and long coding conversations and injects caching breakpoints automatically, claiming up to 90 percent token cost cuts on repeated reads with zero configuration. It targets the exact caching problem YY's own automations already care about, without needing a separate proxy service.

In practice: The most immediately relevant find in this lens, purpose built for exactly this runtime.

For: Claude (Axion). Ships specifically as a Claude Code plugin with a .claude-plugin folder targeting Claude API cache control breakpoints, so it is Claude specific rather than a generic wrapper.

Security3

Quality2

Auditability3

Useful to you5

Useful to community2

Buildable now4

Hermes5

Verdict: test first. Score 24. Built specifically as a Claude Code plugin for a caching problem YY already cares about, small enough to trial in a sandboxed project before wider rollout.

Install: add the plugin via npm install prompt-caching-mcp in a sandboxed test project, or add the .claude-plugin folder directly to a Claude Code project. Review before enabling. Copy

Source · 135 GitHub stars, 7 forks, MIT license, published as the npm package prompt-caching-mcp with active CI and codecov badges, verified by visiting the repo directly on 2026-09-03.

#11

newtest firstBoth runtimes24 / 35

MemPalace repo

A fully local AI memory system built around a palace and drawer metaphor, using ChromaDB internally, that ships an MCP server with 45 tools for reads, writes, knowledge graph operations, and multi agent coordination.

What it does for you: Installs as a CLI plus an MCP server that a Claude Code agent can call directly for persistent storage, cross session recall, and multi agent handoffs through an agent diary and log stream, with no external API calls required since it runs fully local. It ships its own .claude-plugin directory, meaning Claude Code plugin wiring is closer to drop in than most competitors.

In practice: The most exciting fit on paper for a local first Axion and Hermes stack, but the growth curve is fast enough to double check before building on it.

For: Both runtimes. Runs as a local CLI plus an MCP server, so it is reachable from Claude Code or any other MCP capable client without being tied to one vendor's SDK.

Security2

Quality3

Auditability3

Useful to you4

Useful to community3

Buildable now4

Hermes5

Verdict: test first. Score 24. Directly built for Claude Code style agents with a real MCP server and no external API dependency, but star growth from 0 to nearly 59,000 in about 5 months is unusually fast for infrastructure tooling and warrants a closer look at issue quality before committing.

Build #11 MemPalace: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/MemPalace/mempalace. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 58,829 GitHub stars and 7,547 forks as of 2026-09-04, MIT license, created 2026-04-05, latest release v3.9.0 published 2026-08-31 with a weekly release cadence, checked directly via the GitHub REST API.

#12

test firstBoth runtimes24 / 35

Cognee repo

An open source AI memory platform combining a knowledge graph with vector search, packaged as a self hosted engine for persistent agent memory.

What it does for you: Offers a hybrid graph plus vector retrieval pipeline in one package, so YY gets both fact lookup and semantic search without wiring two separate systems together. It ships MCP integrations directly, meaning it can be added to Claude Code as a memory MCP server with less custom glue code than assembling a vector store and graph store separately.

In practice: Feels like the most complete out of the box package for someone who wants graph and vector memory without assembling it themselves.

For: Both runtimes. Ships MCP integrations directly on top of a self hosted graph and vector engine, so it is usable from any MCP capable runtime.

Security3

Quality4

Auditability3

Useful to you4

Useful to community4

Buildable now3

Hermes3

Verdict: test first. Score 24. Fast release cadence and direct MCP support make it worth a real pilot against Mem0 before picking a default memory layer for a Hermes runtime.

Build #12 Cognee: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/topoteretes/cognee. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 30,440 GitHub stars and 2,991 forks, Apache 2.0 license, three releases in two weeks: v1.5.2 on 2026-08-22, v1.5.3 on 2026-08-23, and v1.5.3.dev1 on 2026-08-26, checked directly via the GitHub REST API on 2026-09-04.

#13

test firstBoth runtimes24 / 35

FunASR repo

An open source, MIT licensed speech recognition toolkit from ModelScope supporting streaming automatic speech recognition, voice activity detection, punctuation, and speaker diarization, with a built in MCP server.

What it does for you: Ships an MCP server labeled for Claude and Cursor so YY could add local, self hosted transcription as a tool inside Axion without paying per minute to a cloud speech to text API, useful for transcribing meeting recordings, voice notes, or podcast raw footage before content processing. It also has an OpenAI compatible API mode for wiring into existing pipelines.

In practice: The most directly usable option here for an actual pain point, self hosted transcription of coaching content feeding into the brain.

For: Both runtimes. Ships a self hosted MCP server for transcription plus an OpenAI compatible API mode, so it is usable from Claude Code or any other pipeline without being locked to one vendor.

Security3

Quality4

Auditability3

Useful to you4

Useful to community4

Buildable now3

Hermes3

Verdict: test first. Score 24. Direct MCP integration and a real local transcription need make this worth a small pilot against the current voice note and Mac transcript pipeline before adopting.

Build #13 FunASR: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/modelscope/FunASR. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 20,000 GitHub stars, MIT license for the toolkit code confirmed on the repo license section, with an MCP server and a realtime plugin both linked directly in the README quick start section.

#14

test firstBoth runtimes23 / 35

AG2 repo

A community maintained fork of AutoGen, now shipping a rewritten event driven framework that reached stable v1.0 and is iterating through 1.0.x patch releases, currently v1.0.3.

What it does for you: The 1.0.x line added a SkillPlugin that is spec aligned with agentskills.io, meaning AG2 agents can load the same kind of portable skill packages Axion already uses, plus a feature to serve an AG2 agent as an MCP server with OAuth, which is a direct bridge into YY's existing MCP based tooling.

In practice: The most directly relevant find in the orchestration lens, its skills and MCP server features read like they were built with Axion's setup in mind.

For: Both runtimes. A Python framework that can run standalone or expose itself as an MCP server, so it works whether or not Claude Code is the caller.

Security3

Quality3

Auditability3

Useful to you4

Useful to community3

Buildable now3

Hermes4

Verdict: test first. Score 23. The agentskills.io aligned SkillPlugin and MCP server exposure are worth a hands on spike before deciding whether to depend on it.

Build #14 AG2: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/ag2ai/ag2. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · Latest tagged release is v1.0.3 on the project's GitHub releases page, following v1.0.2, with the SkillPlugin and MCP server features landing in the same recent release cycle.

#15

newtest firstBoth runtimes23 / 35

AgentField repo

An open source execution backend that runs agent functions as durable, callable services with async fire and forget execution, webhooks, streaming, and retries, with no enforced timeout.

What it does for you: Solves the problem of a background agent that needs to run for hours without a client connection, by exposing an async endpoint that queues the job, retries with backoff, and calls a signed webhook when done, which is exactly the shape of an unattended overnight Axion task. It explicitly supports wrapping Claude Code or Codex CLI calls as callable functions, and keeps existing LangGraph or CrewAI logic runnable inside it rather than requiring a rewrite.

In practice: The single most concretely useful spec in this lens for turning a Claude Code call into a fire and forget background job with a webhook callback.

For: Both runtimes. Wraps Claude Code or Codex CLI calls as callable functions but is not itself Claude specific, so it fits any coding agent CLI.

Security3

Quality3

Auditability3

Useful to you4

Useful to community3

Buildable now3

Hermes4

Verdict: test first. Score 23. The async execute plus webhook pattern maps directly onto a real Axion need, worth a small non critical pilot before trusting it with anything time sensitive.

Build #15 AgentField: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/Agent-Field/agentfield. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 2,500 GitHub stars as read from the repo's About panel on 2026-09-03, with a documented changelog and versioned execution restart and run metadata API docs in the repo.

#16

test firstBoth runtimes23 / 35

Pipecat repo

An open source Python framework maintained by Daily for building voice agents, multimodal apps, and realtime AI pipelines, currently at release v1.8.1.

What it does for you: Gives YY a pipeline abstraction to wire speech to text, an LLM, and text to speech services together for a phone or web voice agent, for example a booking or intake bot for MCL, without hand building the audio plumbing. It has WebRTC and telephony transport built in, so it can sit in front of Claude Code style agent logic as the voice front end.

In practice: Feels like the current default choice for anyone assembling a voice agent from parts rather than a single vendor SDK.

For: Both runtimes. A Python pipeline framework that assembles third party speech and LLM services, independent of any single agent runtime.

Security3

Quality4

Auditability3

Useful to you3

Useful to community4

Buildable now3

Hermes3

Verdict: test first. Score 23. Real production traction and an active release cadence, but worth a small prototype before committing given how much the API has changed release to release.

Build #16 Pipecat: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/pipecat-ai/pipecat. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 15,200 GitHub stars, BSD 2 Clause license, latest release v1.8.1 shipped 2026-08-27, confirmed on the GitHub releases page.

#17

newtest firstBoth runtimes22 / 35

Arize Coding Harness Tracing repo

An Apache 2.0 open source library that instruments coding agent harnesses, including Claude Code, Cursor, and Codex, and emits OpenInference spans to Arize AX or Phoenix.

What it does for you: Reconstructs each turn of a Claude Code session as a trace tree, prompts, tool calls, model responses, and subagent runs, and ships that to Phoenix, which is self hostable, so YY can see exactly where an Axion agent run wasted tokens or looped. It targets the specific harness YY already uses rather than a generic LLM SDK, so setup is narrower than instrumenting raw API calls by hand.

In practice: Feels like the right shaped tool at the right time, small and unproven but pointed straight at Claude Code instead of being generic.

For: Both runtimes. Instruments Claude Code, Cursor, and Codex alike and emits vendor neutral OpenInference spans, so it is not exclusive to one runtime.

Security3

Quality2

Auditability3

Useful to you5

Useful to community2

Buildable now3

Hermes4

Verdict: test first. Score 22. Directly targets Claude Code tracing, which nothing else in this issue does natively, but immaturity means a short pilot on one Axion agent before wiring it into the whole system.

Build #17 Arize Coding Harness Tracing: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/Arize-ai/coding-harness-tracing. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · Repo created 2026-03-30, last pushed 2026-09-03, 38 GitHub stars, 25 open issues, Apache 2.0 license, pulled directly from the GitHub API on 2026-09-04.

#18

newtest firstBoth runtimes22 / 35

gh-aw repo

A GitHub built framework for writing scheduled and event triggered agentic workflows in markdown that run inside GitHub Actions using Claude Code, Copilot, Gemini, or Codex as the engine.

What it does for you: Lets YY define a background agent as a markdown file with a cron trigger or repo event, then have it run sandboxed in Actions with safe output guardrails instead of building a custom scheduler and credential store. Directly usable for Axion style overnight jobs if any repo automation moves to GitHub, and its sandboxing model is a reference for hardening a Hermes runtime.

In practice: Feels like the most credible and best resourced entry in this lens since GitHub itself is maintaining it, but the recent security retraction is a real flag on a young project.

For: Both runtimes. Runs inside GitHub Actions and can use Claude Code, Copilot, Gemini, or Codex as the engine, so it is deliberately runtime agnostic.

Security2

Quality4

Auditability3

Useful to you3

Useful to community4

Buildable now3

Hermes3

Verdict: test first. Score 22. High pedigree and star count, but a recent enough vulnerability history means it needs a scoped, low stakes trial before touching anything with real credentials.

Build #18 gh-aw: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/github/gh-aw. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 5,100 GitHub stars, 527 forks, 17,465 commits on main, and a disclosed security advisory GHSA-8h78-hpm7-29gg affecting versions 0.83.3 to 0.85.4 that were retired as a precaution, all confirmed on the live GitHub repo page on 2026-09-03.

#19

newtest firstStandalone tool21 / 35

Muse Code plugin

Meta's first terminal based coding agent, released in beta on 2026-08-05, powered by the Muse Spark 1.2 model with a 1 million token context window.

What it does for you: Runs multiple background subagents each in its own isolated git worktree so parallel changes never collide, which maps directly onto how YY could farm out coding sub tasks for Axion without manual branch juggling. Every tool call and decision writes to a replayable event log, giving a built in audit trail for autonomous runs up to 24 hours and more than 1,000 tool calls, which is the kind of crash recovery a Hermes runtime currently lacks.

In practice: The worktree per subagent plus event log design feels like the most directly copyable idea for a Hermes runtime this week, genuinely new rather than a wrapper.

For: Standalone tool. A closed beta product with its own model and account system, used as a separate tool rather than built into Axion or a Hermes runtime.

Security3

Quality4

Auditability2

Useful to you4

Useful to community3

Buildable now2

Hermes3

Verdict: test first. Score 21. The worktree isolation and event log pattern are worth a hands on trial to see if they solve Axion's current multi agent collision problem, before deciding to adopt or just borrow the pattern.

Install: request Meta Developer beta access at musecodes.io and install the macOS or Linux CLI with an API key. Review before enabling. Copy

Source · 1 million token context window and sustained runs up to 24 hours with more than 1,000 tool calls, confirmed on the musecodes.io product page as of 2026-09-03. Beta launch date of 2026-08-05 confirmed by MarkTechPost and the official Meta Research blog.

#20

newtest firstBoth runtimes19 / 35

inference.sh MCP Server plugin

A remote MCP server listed in the official MCP registry that exposes more than 150 hosted AI apps for image, video, audio, and 3D generation as callable, streamable tools.

What it does for you: Gives YY one MCP connection that fans out to many hosted generation models instead of installing separate SDKs for each provider, useful for carousel, poster, or video pipeline work where several single purpose media MCPs are currently juggled separately.

In practice: An interesting all in one media gateway, but pricing and authentication details need a closer read before trusting an agent to call it unattended.

For: Both runtimes. A remote MCP server reachable from any MCP capable client over HTTP, not exclusive to Claude Code.

Security2

Quality3

Auditability2

Useful to you3

Useful to community3

Buildable now3

Hermes3

Verdict: test first. Score 19. The July 2026 major version bump to 2.0.0 signals active development and it could consolidate several media MCP calls into one, worth a manual test run before wiring into any automated pipeline.

Install: claude mcp add inference-sh --transport http https://api.inference.sh/mcp. Review before enabling. Copy

Source · Confirmed live via the official registry API, version history shows 1.0.0 published 2026-04-13, updated to 2.0.0 on 2026-07-20, both timestamps read directly from the registry's own metadata on 2026-09-03.