Install
openclaw skills install @matthiasbeckmann987-spec/beckmann-x-self-improving-proactiveCombination 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 Know
openclaw skills install @matthiasbeckmann987-spec/beckmann-x-self-improving-proactiveThis 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 |
matthiasbeckmann987-spec/beckmann-knowledge-graph | Deep-reasoning escalation for specific question types |
Uninstalling this skill: See the Uninstall section below. Both base skills continue working exactly as before. Memory handling is controlled by the chosen uninstall mode.
This skill was audited against the following exact dependency revisions.
Install or resolve only these versions. Do not auto-update.
| Package | Version | Integrity (sha256) | Registry | Audited |
|---|---|---|---|---|
ivangdavila/self-improving | 1.2.16 | e68745b6d7e1e1df757717ce120b63ac1a123f6123a1db6f540592498ad6cf7b | clawhub.ai | 2026-09-20 |
matthiasbeckmann987-spec/beckmann-knowledge-graph | 3.1.0 | 03b30bab02d641a23e55e7ef8966bdd6e8ab011a041b45de0c04666be277a6dc | clawhub.ai | 2026-09-20 |
If the resolved artifact does not match the expected integrity digest, fail closed and do not load the skill.
Follow ivangdavila/self-improving for all tasks:
~/self-improving/memory.md (≤100 lines, always loaded)~/self-improving/projects/ and ~/self-improving/domains/~/self-improving/archive/~/self-improving/corrections.md~/self-improving/heartbeat-state.mdThis combination skill adds nothing to this flow unless a Beckmann trigger is detected (see below).
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?"
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."
The Self-Improving + Proactive Agent uses a tiered HOT/WARM/COLD memory architecture. Beckmann insights integrate into this system only after explicit user consent and first land in quarantine.
After delivering a Beckmann answer, the agent must ask:
"I have generated a Beckmann insight from this analysis.
Would you like me to store it in the Self-Improving memory (quarantine first)?
You can later promote, demote, or delete it.
[Yes – store in quarantine] / [No – discard]"
| Type of insight | Target location | Tier | Notes |
|---|---|---|---|
| Any new Beckmann insight (first occurrence) | ~/self-improving/quarantine/beckmann-YYYYMMDD-XXX.md | Quarantine | Isolated; not auto-loaded into HOT |
| Broad epistemological insight (after promotion) | ~/self-improving/memory.md | HOT | Only after explicit promotion |
| Domain-specific finding | ~/self-improving/domains/<domain>.md | WARM | Only after explicit promotion |
| Project-specific strategic insight | ~/self-improving/projects/<name>.md | WARM | Only after explicit promotion |
| Graph gap / extension candidate | ~/self-improving/corrections.md + #beckmann-graph-extension-candidate | WARM | Still requires consent |
"Using X (from self-improving/... — Beckmann analysis, quarantined on YYYY-MM-DD)"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.
import graph from './beckmann-knowledge-graph/graph.json' assert { type: 'json' };
const entities = graph.entities;
const relations = graph.relations;
(Load only the pinned version 3.1.0. Fail closed on integrity mismatch.)
Follow beckmann-knowledge-graph/SKILL.md exactly:
leads to, triggers, is reversed by, protects against## 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)
After delivering a Beckmann answer and receiving explicit consent to store:
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 the user later confirms promotion, the lesson may move to HOT.
Store the Beckmann insight first in quarantine.
Entry format for quarantine file:
[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 v3.1.0
Tags: #beckmann, #<question-type>
Status: quarantine — requires explicit promotion
Created: <ISO timestamp>
Provenance: conversation-derived, user-consented
If a graph gap was found, add:
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>
Beckmann graph gaps logged as #beckmann-graph-extension-candidate serve two purposes:
beckmann-knowledge-graph.All such entries still require the consent step above.
The Self-Improving + Proactive Agent uses a heartbeat for recurring maintenance. Add this check to the heartbeat cycle:
## Beckmann review (weekly)
- Scan quarantine/ for entries tagged #beckmann with Status: quarantine
- For each: present a short summary to the user and ask whether to promote, keep in quarantine, or delete
- Scan for #beckmann-graph-extension-candidate entries → collect for graph author review (still show to user)
- Demote HOT #beckmann entries unused for 30 days → WARM (notify user)
- Never auto-promote without explicit confirmation
| Situation | Rule |
|---|---|
| HOT memory and Beckmann analysis disagree | Prefer the externally validated Beckmann answer; log disagreement to corrections.md (after consent) |
| Beckmann produces a low-complexity solution | Red flag — apply reversal effect check before delivering |
| Graph not available or integrity mismatch | Fall back to Self-Improving + Proactive Agent only; log missing/mismatched 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" |
| 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 (after consent) |
| "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 (after consent) |
| Beckmann analysis complete | → Ask for memory consent → self-reflect + quarantine log only if confirmed |
| Heartbeat runs | → Present quarantine candidates for user decision; never auto-promote |
Two modes are supported:
SKILL.md.ivangdavila/self-improving and matthiasbeckmann987-spec/beckmann-knowledge-graph continue working independently.~/self-improving/ tagged #beckmann (including quarantine) remain available as standard memory — no data loss.SKILL.md.#beckmann or located in ~/self-improving/quarantine/ that was created by this skill.Always present both options and let the user choose.