Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
continuity-kernel
OpenClaw continuity kernel for fail-open llm_input injection, deterministic runtime contracts, and shadow-mode eval receipts.
skill openclawclawhub Free
OpenClaw continuity kernel for fail-open llm_input injection, deterministic runtime contracts, and shadow-mode eval receipts.
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- CHANGELOG.md, README.md, SKILL.md, artifacts/continuity-kernel/p0-evals.json, benchmark.py, contracts.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.2.0
Provenance
- Publisher
- tkuehnl
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
When to use this skill
Use this skill when the user wants to: Inject bounded continuity context into llm_input without manual configuration Persist Soul Card + Mission Ticket state with deterministic runtime contracts (durable default SQLite path, zero-config) Keep agent behavior fail-open if continuity logic or storage has an error Generate reproducible runtime proof receipts for audits and reviews Run shadow-mode evals and append chunk-level quality snapshots
Commands
# Run full test suite python3 -m unittest discover -s tests/continuity-kernel -p 'test_*.py' # Generate deterministic runtime contract proof artifact python3 skills/continuity-kernel/generate_runtime_contract_proof.py # SC-02 core-shadow gate (trace optional, synthetic allowed for this suite) python3 skills/continuity-kernel/run_shadow_eval.py --layer 'Soul Card' --chunk 'SC-02' --suite core-shadow --runs 100 --append artifacts/continuity-kernel/p0-evals.json # SC-02 perturb robustness gate (trace-backed, deterministic selector + size_only) python3 skills/continuity-kernel/run_shadow_eval.py --layer 'Soul Card' --chunk 'SC-02' --suite memoryarena-mini-perturb --perturb-profile deletion --selector-mode deterministic --compaction-policy size_only --runs 100 --trace-jsonl tests/continuity-kernel/fixtures/shadow_eval_trace_memoryarena_mini_perturb.jsonl --append artifacts/continuity-kernel/p0-evals.json # SC-02 perturb robustness gate (trace-backed, dual-route + attention-preserving) python3 skills/continuity-kernel/run_shadow_eval.py --layer 'Soul Card' --chunk 'SC-02' --suite memoryarena-mini-perturb --perturb-profile deletion --selector-mode dual_route_experimental --compaction-policy attention_preserving_experimental --runs 100 --trace-jsonl tests/continuity-kernel/fixtures/shadow_eval_trace_memoryarena_mini_perturb.jsonl --append artifacts/continuity-kernel/p0-evals.json
Options
run_shadow_eval.py options: --layer TEXT β Active P0 layer name --chunk TEXT β Active chunk id/name --suite core-shadow|memoryarena-mini|memoryarena-mini-perturb β Task suite for eval scoring --perturb-profile none|deletion|noise_injection|reorder β Deterministic perturb profile for memoryarena-mini-perturb --selector-mode deterministic|dual_route_experimental β Selector mode tag for A/B eval receipts --compaction-policy size_only|attention_preserving_experimental β Compaction policy label for dropped-field A/B eval comparison --runs N β Number of evaluated shadow runs (default: 100) --trace-jsonl PATH β JSONL file containing observed shadow outcomes (repeatable) --trace-dir PATH β Directory scanned for *.jsonl observed shadow outcomes (repeatable) --append PATH β JSON file path to append snapshot results --allow-synthetic β Permit synthetic fallback for non-core suites when traces are unavailable (forced pass=false) --artifacts-root PATH β Directory for summary receipts (default: ~/.cache/continuity-kernel/p0-evals) Runtime persistence defaults: ContinuityHookAdapter() uses ~/.local/state/continuity-kernel/continuity.db Override default path with CONTINUITY_KERNEL_DB_PATH Use :memory: only as explicit opt-in test mode
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs2 Scripts1 Config
- SKILL.md
- CHANGELOG.md
- README.md
- benchmark.py
- contracts.py
- artifacts/continuity-kernel/p0-evals.json