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Skill Forge Maintainers
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v1.0.0 Forge Console
Add a product-level Skill Forge console with doctor, demo, forge, evolve, install, uninstall, feedback, replay, release-check, and version commands. Keep the existing lower-level scripts as stable automation interfaces.
Promote the package to v1.0.0, document ClawHub-installed console usage, add Forge Console reference docs, and extend release checks with console doctor and demo smoke coverage.
Copy file name to clipboardExpand all lines: README.md
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@@ -13,10 +13,19 @@ This repository contains the `skill-forge` OpenClaw-compatible skill. It also su
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`skill-forge` is a milestone self-improvement product for OpenClaw-style agents.
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Current version: `v0.5.0 "Signed Gate"`.
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Current version: `v1.0.0 "Forge Console"`.
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It turns repeated capability gaps into reviewed skill candidates. The product deliberately separates learning, generation, validation, and installation so an agent can improve itself without silently polluting its own skill set.
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`v1.0.0` introduces the Forge Console, a single product entry point over the full lifecycle:
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```bash
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python3 skill-forge/scripts/skill_forge.py doctor --json
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ClawHub may show a safety warning because this skill includes Telegram approval calls and local install/rollback scripts. Review the source first; for non-interactive installs, pass `--force` only after review.
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After a ClawHub install, run the console from the installed package:
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```bash
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python3 ~/.openclaw/workspace/skills/skills-forge/scripts/skill_forge.py doctor --json
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- Records later usage feedback and proposes reviewed skill updates instead of self-mutating installed skills.
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- Runs scheduled nightly health reviews during sleep hours and can propose safe update candidates.
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- Builds redacted replay cases from feedback and blocks update candidates that regress on replay evaluation.
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- Provides a unified Forge Console (`scripts/skill_forge.py`) for doctor checks, demos, generation, signed install plans, feedback capture, replay checks, and release gates.
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## Repository Layout
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│ ├── detect_skill_opportunities.py
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│ ├── evaluate_skill_candidate.py
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│ ├── forge_pipeline.py
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│ ├── skill_forge.py
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│ ├── generate_skill_scaffold.py
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│ ├── validate_skill_candidate.py
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│ ├── install/
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Run the plan-only pipeline (no installs, no Telegram, no secrets needed):
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-`v0.4.2 "Telegram Gate"`: mandatory Telegram approval for install mutations
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-`v0.4.3 "Safety Tightening"`: safe skill slug containment for evolution updates and clearer registry safety posture
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-`v0.5.0 "Signed Gate"`: HMAC-signed approval tokens bound to skill identity and source content hash; missing or non-skill sources are refused before token issuance and before install mutation; dry-run approvals can no longer install or claim Telegram audit; replay regression gate compares candidate against installed baseline; manifest writes are atomic and `flock`-locked; redactor covers IPv4/IPv6, phone numbers, JWTs, common cloud/Git tokens, Telegram bot tokens, and PEM private keys
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-`v1.0.0 "Forge Console"`: product-level command surface with doctor, demo, forge, evolve, install, uninstall, feedback, replay, release-check, and version commands; release checks cover the console smoke path
Copy file name to clipboardExpand all lines: skill-forge/SKILL.md
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Use this skill to turn repeated demand into a reviewed skill candidate.
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Current version: `v0.5.0 "Signed Gate"`.
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Current version: `v1.0.0 "Forge Console"`.
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## Core jobs
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7. Record feedback from later usage and propose reviewed updates instead of mutating installed skills directly.
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8. Provide the Somnia runtime used by scheduled nightly review to find skills with bugs, weak scores, or update-worthy feedback.
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9. Use redacted replay cases to check whether candidates actually cover real feedback-derived tasks.
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10. Provide a product console (`scripts/skill_forge.py`) so agents can run doctor checks, demos, forge flows, evolution, feedback capture, replay, and release gates from one entry point.
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## Trigger Cues
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## Commands
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### Forge Console
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Prefer the product console for normal use:
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```bash
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python3 {baseDir}/scripts/skill_forge.py doctor --json
short_description: "Detect, scaffold, validate, and signed-gate skill installs"
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default_prompt: "Turn a repeated capability gap into a reviewed skill candidate. Detect from .learnings, scaffold by profile, validate and score, run hidden smoke evaluation, and require a Telegram-issued signed approval token (HMAC-bound to skill name, target, method, source path, and source content hash) before any install or update mutation."
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short_description: "Forge Console for skill creation, validation, replay, and signed-gate installs"
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default_prompt: "Use the Forge Console to turn repeated capability gaps into reviewed skill candidates. Start with doctor/demo when onboarding, then forge, validate, replay, and require a Telegram-issued signed approval token (HMAC-bound to skill name, target, method, source path, and source content hash) before any install or update mutation."
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