cognitum.one
219 published Skills
219 Skills · 1 repository
Machine Learning
neural-train
Train SONA + MicroLoRA neural patterns from successful task completions; runs the DISTILL + CONSOLIDATE phases of the 4-step pipeline
Curated from public sources. This profile has not been claimed.
github.com/ruvnet/claude-flow219 Skills · 1 repository
1 source219 standalone skills219 published skills
Developer Tools
intelligence-transfer
Publish or fetch learned patterns across projects via IPFS (Pinata) -- the cross-project pattern transfer that hooks_transfer enables
Developer Tools
intelligence-route
Route tasks via the 3-tier model selector and learned patterns; emits a routing rationale via hooks_explain
Developer Tools
research-synthesize
Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations
Developer Tools
horizon-track
Track long-horizon objectives across multiple sessions with milestone checkpoints, progress persistence, and drift detection
Developer Tools
goal-plan
Create and execute Goal-Oriented Action Plans (GOAP) with precondition analysis, cost optimization, and adaptive replanning
Frontend
dossier-collect
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
Frontend
deep-research
Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings
AI Agents
federation-status
Show federation health — peers, sessions, trust levels, and message metrics. Use when the user asks "is federation healthy?", "show peers", "federation status", or wants to inspect cross-installation agent connectivity.
Backend
federation-init
Initialize federation on this node — generate keypair and configure peers
Governance
federation-audit
Query federation audit logs with compliance filtering
Developer Tools
doc-gen
Generate and maintain documentation with drift detection. Use when the user asks to write/update/refresh docs, detect doc drift against code, or schedule recurring documentation maintenance.
Backend
api-docs
Generate API documentation from source code with JSDoc and OpenAPI support
Backend
deepseek-reason
Reasoning-mode completion against DeepSeek's `deepseek-reasoner` model (R1) via /v1/chat/completions. Surfaces the model's chain-of-thought (`reasoning_content`) separately from the final answer (`content`), so callers can display or discard the CoT without re-parsing. Reads DEEPSEEK_API_KEY; degrades gracefully (exit 0 with status:degraded envelope) when unset or the API is unreachable. Ignores temperature/top_p per DeepSeek's spec for reasoner models.
Generative AI
deepseek-chat
One-shot chat completion against DeepSeek's `deepseek-chat` model via the OpenAI-compatible /v1/chat/completions endpoint. Reads DEEPSEEK_API_KEY from the environment; degrades gracefully (exit 0 with a JSON status:degraded envelope) when the key is missing or the API is unreachable. Use for non-reasoning tasks — summarization, extraction, quick classification — where deepseek-reasoner would be overkill.
Developer Tools
ddd-validate
Validate domain boundaries -- detect cross-context import violations and aggregate invariant issues. Use when auditing a DDD codebase for leaks between bounded contexts, before merging cross-cutting changes, or as a CI gate to catch boundary erosion early.
Infrastructure
ddd-context
Create and manage a DDD bounded context with standard directory structure. Use when starting a new subdomain, splitting a monolith into bounded contexts, or scaffolding the domain/application/infrastructure layout for a fresh module.
UI Design
ddd-aggregate
Scaffold an aggregate root with entity, value objects, repository interface, domain events, and test stubs. Use when adding a new aggregate to an existing bounded context, modeling a new business concept that owns invariants, or generating the boilerplate for an entity + repo + events triplet.
AI Agents
daa-agent
Create and adapt Dynamic Agentic Architecture agents that learn and evolve
AI Agents
cognitive-pattern
Define and manage cognitive patterns for agent reasoning and decision-making
AI Agents
cost-trend
Read every docs/benchmarks/runs/*.json and surface drift in win rate, latency, escalation rate, and LLM-baseline cost over time
AI Agents
cost-track
Auto-capture per-session token usage from the Claude Code session jsonl and persist to the cost-tracking namespace
Planning
cost-summary
Single-shot programmatic dump of all cost data — total spend, per-tier, top session, budget status, federation aggregate. JSON or markdown.
Developer Tools
cost-session
Per-message cost breakdown within a single session. The drill-down companion to cost-anomaly — when an outlier session is flagged, this surfaces the specific expensive messages so operators can see whether the cost came from output tokens, cache writes, or model escalations.