Skill: matthiasbeckmann987-spec/beckmann-x-self-improving-proactive (version 1.0.0)

\--- name: beckmann-x-self-improving-proactive version: 1.0.0 description: "Combination skill that adds the Beckmann Knowledge Graph as a deep-reasoning escalation layer on top of the Self-Improving + Proactive Agent (ivangdavila). Everyday tasks run through the Self-Improving + Proactive Agent as usual. This skill defines exactly when and how to switch to the Beckmann Knowledge Graph and how to feed insights back into hot/warm/cold memory. Uninstalling this skill leaves the Self-Improving + Proactive Agent fully intact." author: matthiasbeckmann987-spec license: MIT-0 requires: "ivangdavila/self-improving, matthiasbeckmann987-spec/beckmann-knowledge-graph" tags: "meta-skill, combination, beckmann-logic, self-improvement, proactive, orchestration" --- # Beckmann × Self-Improving + Proactive Agent — Combination Skill ## Purpose This skill connects two independent skills without modifying either one: |Skill|Role here| |-|-| |`ivangdavila/self-improving`|**Default engine** for all tasks — with proactive memory and self-reflection| |[REDACTED_SECRET]|**Deep-reasoning escalation** for specific question types| **Uninstalling this skill:** Remove this SKILL.md. Both base skills continue working exactly as before. Memory in `\~/self-improving/` is not affected. \--- ## Default Behaviour: Self-Improving + Proactive Agent Runs Everything Follow `ivangdavila/self-improving` for all tasks: * HOT memory in `\~/self-improving/memory.md` (≤100 lines, always loaded) * WARM memory in `\~/self-improving/projects/` and `\~/self-improving/domains/` * COLD memory in `\~/self-improving/archive/` * Log corrections to `\~/self-improving/corrections.md` * Promote patterns after 3x in 7 days → HOT * Demote after 30 days unused → WARM; after 90 days → COLD * Self-reflect after significant tasks (CONTEXT / REFLECTION / LESSON format) * Maintain heartbeat state in `\~/self-improving/heartbeat-state.md` This combination skill adds **nothing** to this flow unless a Beckmann trigger is detected (see below). \--- ## Beckmann Escalation Triggers Escalate to `beckmann-knowledge-graph` when the question matches **one or more** of these categories: |#|Category|Example signals| |-|-|-| |1|**Open scientific / philosophical question**|"What is consciousness?", "Does free will exist?", "What is dark energy?"| |2|**Apparent paradox**|Question contains an internal contradiction or "impossible" framing| |3|**High-complexity long-horizon forecast**|"How will AI change democracy in 20 years?", "What are AGI systemic risks?"| |4|**Strategic dead end**|Obvious solutions have repeatedly failed; dominant expectations seem to block progress| |5|**AI safety / architecture question**|Dangerous vs. safe AI design, value alignment, AI-human symbiosis| |6|**Epistemological limit question**|"Is it even possible to know X?", "Is a presupposition in this question false?"| **Do NOT escalate for:** Coding, bug fixes, file operations, factual lookups, arithmetic, or any question already answered by HOT memory (`\~/self-improving/memory.md`). **Uncertain?** Apply the Complexity Check: > "Would a highly intelligent person answer this differently after a week > of thinking about hidden assumptions in the question?" * Yes → suggest Beckmann. No → stay on default path. \--- ## Proactive Suggestion (Before Escalating) If a Beckmann trigger is detected, the agent **must not escalate silently or automatically**. Instead, it first informs the user and waits for confirmation. **Suggested phrasing:** > "Your question touches on \[open scientific question / an apparent paradox / > a high-complexity forecast — pick the matching category]. I have access to > the Beckmann Knowledge Graph, a structured reasoning framework for exactly > this type of question. Would you like me to apply it? It will take a bit > longer than a standard answer, but will analyse hidden assumptions and > offer a more structured response." **Then wait.** Only escalate if the user confirms. If the user declines, answer with standard knowledge and note: > "I've answered with standard reasoning. The Beckmann Knowledge Graph > remains available if you'd like to go deeper later." \--- ## Integration with Proactive Memory The Self-Improving + Proactive Agent uses a tiered HOT/WARM/COLD memory architecture. Beckmann insights integrate into this system as follows: ### Where Beckmann results are stored |Type of insight|Target location|Tier| |-|-|-| |Broad epistemological insight (applies across domains)|`\~/self-improving/memory.md`|HOT| |Domain-specific Beckmann finding (e.g. AI safety, physics)|`\~/self-improving/domains/<domain>.md`|WARM| |Project-specific strategic insight|`\~/self-improving/projects/<name>.md`|WARM| |Graph gap / extension candidate|`\~/self-improving/corrections.md` + `#beckmann-graph-extension-candidate` tag|WARM| |Insight not yet validated (first occurrence)|`\~/self-improving/corrections.md`|WARM| ### Promotion rules for Beckmann insights Follow the standard promotion rules of `ivangdavila/self-improving`: * Same Beckmann insight applied successfully 3x → promote to HOT * HOT Beckmann insight unused 30 days → demote to WARM * Always cite source: `"Using X (from self-improving/domains/epistemology.md — Beckmann analysis)"` \--- ## Escalation Protocol (Step by Step) ### 1 — Check HOT memory first Before loading the graph, scan `\~/self-improving/memory.md` for entries tagged `#beckmann`. If a directly relevant insight exists there, use it — and note that it came from a previous Beckmann analysis. Only load the full graph if no relevant HOT entry exists. ### 2 — Load the graph ```javascript import graph from './beckmann-knowledge-graph/graph.json' assert { type: 'json' }; const entities = graph.entities; const relations = graph.relations; ``` ### 3 — Apply the 6-step Beckmann protocol Follow `beckmann-knowledge-graph/SKILL.md` exactly: 1. Classify the question (epistemological / paradox / forecast / strategic / AI safety) 2. Extract relevant entities 3. Trace relation paths — pay attention to `leads to`, `triggers`, `is reversed by`, `protects against` 4. Apply Beckmann Logic (Problem Level → Low vs. High Complexity Solution → Reversal Effect check) 5. Apply epistemological grounding (model vs. external reality, known limits) 6. Structure output in Graph-Grounded Answer format (see below) ### 4 — Deliver the answer ``` ## Graph-Grounded Answer \*\*Problem framing\*\* (what the question really asks, after presupposition analysis) \*\*Relevant graph nodes used:\*\* - \[Entity ID] — \[why relevant] \*\*Reasoning path\*\* (relation chain that leads to the answer) \*\*Answer\*\* (the actual response, informed by the graph logic) \*\*Confidence and limits\*\* (what the graph cannot resolve, and why) \*\*New questions opened\*\* (what the next problem level is) ``` ### 5 — Self-reflect (Proactive Agent style) After delivering a Beckmann answer, add a self-reflection entry: ``` CONTEXT: Beckmann analysis — <question type> REFLECTION: <what the graph revealed that standard reasoning would have missed> LESSON: <what to apply next time a similar question appears> ``` If this lesson applies 3x → promote to HOT memory. ### 6 — Log to tiered memory Store the Beckmann insight in the appropriate tier (see Integration table above). **Entry format for `corrections.md` (first occurrence):** ```markdown \[BKM-YYYYMMDD-XXX] Question type: <paradox | forecast | epistemological | strategic | ai-safety> Graph nodes used: <comma-separated entity IDs> Key insight: <most important finding> New actual level: <what the problem level becomes after this analysis> Source: beckmann-knowledge-graph v<version> Tags: #beckmann, #<question-type> Status: tentative — promote after 3x validation ``` **If a graph gap was found, add:** ```markdown Tags: #beckmann, #beckmann-graph-extension-candidate Extension-Type: new\_entity | new\_relation | new\_case\_study | new\_paradox Suggested-Entity-ID: <proposed entity name> Suggested-Entity-Type: <type from graph schema> Suggested-Description: <draft description for the graph author> ``` \--- ## Graph Extension Feedback Loop Beckmann graph gaps logged as `#beckmann-graph-extension-candidate` serve two purposes: 1. **Now:** Structured record for the graph author to review when planning the next version of `beckmann-knowledge-graph`. 2. **Future:** When a future version of the Beckmann Knowledge Graph supports agent-driven graph extension, entries tagged `#beckmann-graph-extension-candidate` in `corrections.md` will serve as the structured input for that autonomous extension process. The logging format is designed to be machine-readable from day one. \--- ## Heartbeat Integration The Self-Improving + Proactive Agent uses a heartbeat for recurring maintenance. Add this check to the heartbeat cycle: ```markdown ## Beckmann review (weekly) - Scan corrections.md for entries tagged #beckmann with Status: tentative - For each: has this insight been applied 3x? → promote to HOT - Scan for #beckmann-graph-extension-candidate entries → collect for graph author review - Demote HOT #beckmann entries unused for 30 days → WARM ``` \--- ## Conflict Resolution |Situation|Rule| |-|-| |HOT memory and Beckmann analysis disagree|Prefer the externally validated Beckmann answer; log disagreement to `corrections.md`| |Beckmann produces a low-complexity solution|**Red flag** — apply reversal effect check before delivering| |Graph not available|Fall back to Self-Improving + Proactive Agent only; log missing graph to `corrections.md`| |HOT memory already contains a `#beckmann` entry for this question|Use the HOT entry; skip full graph load; note "from prior Beckmann analysis"| \--- ## Quick Reference |Signal|Action| |-|-| |Coding error, failed command, user correction|→ Self-Improving + Proactive Agent: log to corrections.md| |"What is consciousness / free will / dark energy?"|→ Escalate to Beckmann| |"How will X change in 20 years?"|→ Escalate to Beckmann (forecast)| |"Why does X always fail even though it seems logical?"|→ Escalate to Beckmann (reversal effect suspected)| |"Is it even possible to know X?"|→ Escalate to Beckmann (epistemological limit)| |Graph entity not found|→ Log as `#beckmann-graph-extension-candidate` in corrections.md| |Beckmann analysis complete|→ Self-reflect + log to tiered memory| |Heartbeat runs|→ Review #beckmann entries for promotion / demotion| \--- ## Uninstall 1. Delete this `SKILL.md`. 2. Both `ivangdavila/self-improving` and [REDACTED_SECRET] continue working independently. 3. Memory entries in `\~/self-improving/` tagged `#beckmann` remain available to the Self-Improving + Proactive Agent as standard memory — no data loss.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)