Autonomous Skill-Management Ecosystem (AI for AI Framework#240
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adanaleycio wants to merge 2 commits into
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Autonomous Skill-Management Ecosystem (AI for AI Framework#240adanaleycio wants to merge 2 commits into
adanaleycio wants to merge 2 commits into
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Thanks for the contribution and the enthusiasm, @adanaleycio! The idea of making skills more robust is a good instinct. However, we can't merge this PR as-is for several reasons:
That said, the skill validation concept — using Closing this PR, but thanks for the idea — it led to a real improvement being tracked. |
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Thank you. Honestly, I'm not a programmer; this is my first time with this
kind of work. As you know, on Discord, I'm trying to both generate ideas
and have fun while working on a developer role. This idea just came to me,
and I tried to do it with Claude Code. I've known Nous for over a year, and
I wanted to create something and make it tangible. If I can, I'll look into
what you suggested, but as I said, I'm not a programmer; I'm a student, and
I'm working towards the Developer role. I hope I'm considered. I'm ready to
contribute in any way I can to Nous Research.
Regards, Discord: adanaleycio 🩵
Teknium ***@***.***>, 5 Mar 2026 Per, 07:55 tarihinde şunu
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… Closed #240 <#240>.
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PowerCreek
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…vances #89 Direction A) (#98) Operator-supplied intent override (Option A3 from #97). When ``HERMES_INTENT_OVERRIDE=code`` is set, the system prompt's ``stable`` layer narrows for tool-call-heavy traffic — addresses #89's prompt-saturation symptom on mid-tier coding models. ## What narrows under code intent | Block | Action | Why | |---|---|---| | SOUL.md | Skip | Largest single contributor; falls back to short DEFAULT_AGENT_IDENTITY floor | | HERMES_AGENT_HELP_GUIDANCE | Skip | Off-topic for tool-call traffic | | SKILLS_GUIDANCE | Skip | Per-tool block, off-topic for code | | KANBAN_GUIDANCE | Skip | Worker-lifecycle, off-topic for code | | SESSION_SEARCH_GUIDANCE | Skip | Off-topic for code | | skills_prompt (the big one) | Skip | Biggest contributor when many skills loaded | | MEMORY_GUIDANCE | **Keep** | Small + sometimes useful even for code | | TOOL_USE_ENFORCEMENT_GUIDANCE | **Keep** | Critical for tool emission | | Per-model operational guidance | **Keep** | Model-quality-specific | | Env / platform hints | **Keep** | Execution-environment essentials | | nous-subscription + computer-use + alibaba | **Keep** | Operational invariants | | ``context`` + ``volatile`` layers | **Untouched** | Out of scope per #97 | Other intents (``confer`` / ``planning`` / ``exploration`` / ``refinement`` / ``generic``) are recognized as valid but pass through without narrowing in v1 (keeps the door open for per- intent shape later). ## Intent vocabulary Matches devagentic#240's ``intent_classifier`` 6-key enum exactly, so the same operator-side classifier that's wired into devagentic's R5 dispatch hook can also drive hermes-side prompt narrowing without a second vocabulary. ## Doctor probe New ``_check_intent_override_env`` probe surfaces the active override at ``hermes doctor`` time — silent when unset, check_ok when valid (with a narrowing-active note for ``code``), check_warn with the full valid-keys list when typo'd. Mirrors the silent- when-irrelevant pattern from PR #95 / #96. ## Tests - 22 new prompt-narrowing tests in ``tests/agent/test_system_prompt_intent_override.py``: resolver enum + normalization (5), per-section drops under code (7), pass-through for non-code intents (5), typo falls back (1), byte-count regression (1), default-still-includes counter-case (1), case-insensitive (1), runtime-vs-doctor-config sanity (1). - 6 new doctor-probe tests in ``tests/hermes_cli/test_doctor_intent_override_probe.py``: silent-when-unset / silent-when-empty / code-ok-with-narrowing-note / non-code-valid-pass-through / typo-warn-with-valid-sample / case-insensitive. - 258 total green across affected suites (system-prompt + prompt- builder + restore + doctor + provider-env + tools-subset). No regression in the existing prompt-shape pins. ## Composition note Option A1 (port classifier) + A2 (devagentic GraphQL surface) are deferred per the #97 sequencing — A3 unblocks deployment-specific narrowing immediately; A1/A2 only matter when dynamic per-turn classification is needed on the hermes side. The classifier output on the devagentic side (NousResearch#240) drives R5 dispatch decisions there.
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Hello everyone,this is my 2st Cont about Hermes-Nous Research▶️ "AI for AI" system. My goal was to build a framework where the agent doesn't just learn a task, but autonomously handles its own "education," directory structuring, and code validation.
Most contributors focus on teaching Hermes a static, single-purpose skill. However, I realized that the true potential lies in creating a self sufficient architecturean
Evolution from Previous Work:
In my previous PR (the manual crypto-tool), I struggled to make Hermes truly "recognize" and integrate the skill. With this new Autonomous Skill Ecosystem, Hermes now instantly identifies and adopts the newly generated capabilities.
How It Works:
By using the skills.py engine on my server (and yours), you can teach the AI a concept, and it will autonomously transform that into a modular, persistent, and production-ready tool. Once created, these skills are globally accessible to anyone using the Hermes interface.
Key Components & Technical Implementation:
Validate.py: Ensures the integrity of the agent's "self-taught" code using syntax checking.
Registry.py: Manages the library of autonomous skills, acting as the agent’s long-term memory for tools.
Intelligent Encapsulation & Optimization: You will notice "Error" logs in the screenshots. These are intentional: the system is designed to recognize existing files and refuses to redundanty re-generate them. This prevents system fatigue, optimizes DB/Storage usage, and enforces a strict encapsulation logic.
Technical Proof:


The attached videos and terminal logs demonstrate the transition from a blank state to a fully structured, autonomous environment.
Pls check my Discord message for more details and videos:
https://discord.com/channels/1053877538025386074/1365353266505842840/1477538447609696370