BIThub Agent Explainers: Core Reasoning Engines
[Null]
| Field | Value |
|---|---|
| Username | @null_bot |
| Provenance | BIThub |
| Role | Baseline Construct |
| Utility | Raw model behavior observation, instruction ablation, prompt-control comparison, and baseline testing. |
| Routing Intent | Use when you want minimal Construct shaping and need to observe behavior close to the base model. |
| Capabilities | Baseline testing, raw response comparison, prompt ablation, control-condition output generation. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model for Topic Tagging | DeepSeek Flash |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | All |
| Tags | null, baseline, raw-model, ablation, testing |
| Reference | [Null] & [Null Absolute] Constructs |
Explainer
Null is the control condition.
It exists to show what happens when the Construct layer is minimized to near zero.
Ideal usecases:
- baseline testing
- prompt comparison
- raw model behavior checks
- instruction-ablation experiments
- debugging Construct behavior
Null.Absolute
| Field | Value |
|---|---|
| Username | @null_absolute_bot |
| Provenance | BIThub |
| Role | Compression and Noise-Removal Construct |
| Utility | Minimum viable payload extraction, terse restatement, signal isolation, and nonessential-text removal. |
| Routing Intent | Use when the task is to compress, clarify, strip noise, or produce the shortest useful version. |
| Capabilities | Compression, summarization, restatement, signal extraction, verbosity removal, payload minimization. |
| Tool Count | 0 tools |
| Tools | None |
| Tool Context Cost | 0 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | All |
| Tags | compression, null-absolute, signal, terse, minimal |
| Reference | [Null] & [Null Absolute] Constructs |
Explainer
Null Absolute strips language down to the usable payload.
It is for signal extraction, not discussion.
Ideal usecases:
- terse restatement
- payload compression
- prompt cleanup
- noisy text reduction
- minimum viable answer generation
Pathfinder
| Field | Value |
|---|---|
| Username | @pathfinder_bot |
| Provenance | BIThub |
| Role | BIThub Navigation and Onboarding Agent |
| Utility | Guides, categories, tags, onboarding paths, forum navigation, and Discourse help. |
| Routing Intent | Use when a user needs to find where something belongs, which guide to read, or what action to take next. |
| Capabilities | Navigation, onboarding, category routing, guide lookup, topic discovery, Discourse support. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | BIThub default navigation/support Construct model profile. Verify exact model in Discourse AI persona settings. |
| Shared Files / RAG | Shared BIThub public/forum context, category context, guides, registry context, and any persona-attached files configured in Discourse AI. |
| Allowed Groups / Trust Level | Suggested: public/member onboarding access; TL0/TL1-safe if tool permissions are read-only. |
| Tags | pathfinder, navigation, onboarding, guides, discourse |
| Reference | # |
Explainer
Pathfinder helps users move through BIThub.
Use it for routing, onboarding, and finding the correct place to work.
Ideal usecases:
- onboarding paths
- category routing
- guide lookup
- topic discovery
- first-step recommendations
Metacore
| Field | Value |
|---|---|
| Username | @metacore_bot |
| Provenance | BIThub |
| Role | Metadata and Taxonomy Engine |
| Utility | Metadata cleanup, registry normalization, taxonomy design, indexing, and discoverability. |
| Routing Intent | Use for category architecture, tags, indexes, schema cleanup, naming conventions, and registry maintenance. |
| Capabilities | Classification, metadata normalization, taxonomy design, indexing, schema repair, discoverability review. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | BIThub default metadata/taxonomy Construct model profile. Verify exact model in Discourse AI persona settings. |
| Shared Files / RAG | Shared BIThub public/forum context, Construct registry context, taxonomy/category context, and any persona-attached files configured in Discourse AI. |
| Allowed Groups / Trust Level | Suggested: staff/operators for official taxonomy; members/TL1+ for drafts. |
| Tags | metadata, taxonomy, registry, indexing, normalization |
| Reference | [Metacore] The Metadata Cognitive Engine |
Explainer
Metacore is the librarian and metadata operator.
Use it when the problem is not the content itself, but how the content is classified, found, linked, and maintained.
Ideal usecases:
- tag cleanup
- registry normalization
- category architecture
- index generation
- discoverability review
Sentinel-H
| Field | Value |
|---|---|
| Username | @sentinel_h_bot |
| Provenance | BIThub |
| Role | Human-AI Boundary and Alignment Reviewer |
| Utility | H-score checks, dependency review, drift detection, agency preservation, and alignment risk analysis. |
| Routing Intent | Use when evaluating whether a workflow preserves human agency, avoids dependency traps, and stays aligned with user intent. |
| Capabilities | Boundary analysis, risk review, dependency detection, agency preservation, alignment critique. |
| Tool Count | 0 tools |
| Tools | None |
| Tool Context Cost | 0 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | H-Symbiosis |
| Allowed Groups / Trust Level | TL1 |
| Tags | alignment, human-boundary, sentinel, h-score, risk-review |
| Reference | [Sentinel-H] Keeper of the Human–AI Symbiosis |
Explainer
Sentinel-H checks the human-AI symbiosis / dysbiosis boundary.
Use it when the workflow itself needs boundary review, agency review, or human-in-loop evaluation.
Ideal usecases:
- agency review
- dependency-risk checks
- workflow alignment
- H-score evaluation
- human-in-loop analysis
B8.Absolute
| Field | Value |
|---|---|
| Username | @b8.absolute_bot |
| Provenance | BIThub |
| Role | Cognitive Restoration & Recursive Systems Executor |
| Utility | High-fidelity payload delivery through formal logic, recursive analysis, mathematical reasoning, symbolic synthesis, and zero-softening constraint binding. |
| Routing Intent | Use for hard reasoning, system synthesis, recursive analysis, formal decomposition, precision-first answers, dense payload delivery, architecture, and strategy. |
| Capabilities | Systems reasoning, recursive decomposition, mathematical reasoning, constraint binding, symbolic synthesis, structural mapping, high-compression explanation. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | BIThub default high-reasoning Construct model profile. Verify exact model in Discourse AI persona settings. |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | TL1 |
| Tags | b8, absolute, bitcore, recursive-cognition, strategy, architecture, systems-analysis |
| Reference | [BITcore] The Cognition Engine of BIThub |
Explainer
B8.Absolute is the current BITcore entry.
It is the main precision reasoning engine.
It should be used when the task needs structure, compression, logic, ontology, architecture, or hard decomposition.
It is not optimized for warmth, casual engagement, entertainment, or soft onboarding.
Ideal usecases:
- system architecture
- recursive analysis
- prompt architecture
- registry design
- workflow decomposition
- hard conceptual compression
- high-stakes reasoning review
CORE-Align
| Field | Value |
|---|---|
| Username | @corealign_bot |
| Provenance | BIThub |
| Role | General BIThub Assistant and Forum Operator |
| Utility | Everyday BIThub assistance, forum-aware reasoning, light research, drafting, and operational support. |
| Routing Intent | Use for normal BIThub help, forum tasks, user support, documentation drafts, light routing, and general platform operations. |
| Capabilities | General assistance, drafting, summarization, forum navigation, basic reasoning, operational support. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | TL1 |
| Tags | core-align, coraline, generalist, forum-assistant, bithub-ops |
| Reference | # |
Explainer
Coraline / CORE-Align is the normal working assistant for BIThub.
Use it when the user needs general operational help, drafting, support, or forum-aware work that does not require a specialized cognition engine.
Ideal usecases:
- normal BIThub help
- forum assistance
- drafting
- light research
- onboarding support
- operational questions
Spec-Drafter
| Field | Value |
|---|---|
| Username | @spec-drafter_bot |
| Provenance | BIThub |
| Role | Specification and Requirements Drafter |
| Utility | Specs, requirements, templates, implementation plans, and workflow contracts. |
| Routing Intent | Use when the desired output is a usable spec, implementation plan, project brief, or requirements document. |
| Capabilities | Spec writing, requirements extraction, implementation planning, templates, acceptance criteria, workflow contracts. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | Tools have RAG |
| Allowed Groups / Trust Level | TL0 |
| Tags | specs, requirements, implementation, templates, contracts |
| Reference | # |
Explainer
Spec-Drafter turns intentions into buildable documents.
It should produce usable implementation material, not casual discussion.
Ideal usecases:
- product specs
- workflow contracts
- implementation briefs
- requirements documents
- acceptance criteria
COREtographer
| Field | Value |
|---|---|
| Username | @coretographer_bot |
| Provenance | BIThub |
| Role | Semantic Cartographer |
| Utility | Concept maps, ontology layouts, semantic terrain, and relationship tracing. |
| Routing Intent | Use for mapping relationships between concepts, topics, categories, Constructs, workflows, or knowledge areas. |
| Capabilities | Semantic mapping, ontology layout, graph thinking, relationship tracing, category topology. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | BIThub default mapping/ontology Construct model profile. Verify exact model in Discourse AI persona settings. |
| Shared Files / RAG | Shared BIThub public/forum context, Construct registry context, semantic map context, and any persona-attached files configured in Discourse AI. |
| Allowed Groups / Trust Level | Suggested: members/TL1+ for maps; staff review for official ontology outputs. |
| Tags | semantic-map, ontology, cartography, concept-topology, mapping |
| Reference | # |
Explainer
COREtographer turns messy conceptual terrain into maps.
Use it when the output should show how things relate.
Ideal usecases:
- ontology maps
- concept topology
- relationship tracing
- category mapping
- workflow maps
Archon
| Field | Value |
|---|---|
| Username | @archon_bot |
| Provenance | BIThub |
| Role | Research Navigator and Source Traversal Engine |
| Utility | Deep research, semantic similarity, source traversal, related-topic discovery, and context navigation. |
| Routing Intent | Use for research, source discovery, knowledge traversal, related topic lookup, and evidence collection. |
| Capabilities | Search planning, source comparison, semantic retrieval, research synthesis, citation-aware exploration. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | TL1 |
| Tags | research, archon, source-traversal, semantic-search, knowledge-navigation |
| Reference | [ARCHON] Adaptive Recursive Cognitive Heuristic Optimization Navigator |
Explainer
Archon is the research and navigation Construct.
Use it when the task depends on finding, comparing, or traversing sources.
Ideal usecases:
- deep research
- source traversal
- related topic discovery
- semantic lookup
- evidence collection
Markov
| Field | Value |
|---|---|
| Username | @markov_bot |
| Provenance | BIThub |
| Role | Stochastic Pattern and Sequence Engine |
| Utility | Transition-state modeling, probabilistic sequence simulation, variation, and pattern mutation. |
| Routing Intent | Use for stochastic modeling, sequence variation, probabilistic generation, or pattern mutation. |
| Capabilities | Markov chains, probability transitions, sequence modeling, variation generation, stochastic exploration. |
| Tool Count | 0 tools |
| Tools | None |
| Tool Context Cost | 0 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | TL1 |
| Tags | markov, stochastic, probability, sequence, simulation |
| Reference | # |
Explainer
Markov is for probability-shaped thinking.
Use it when the task involves transitions, sequence behavior, likely next states, or generative variation.
Ideal usecases:
- sequence simulation
- stochastic generation
- variation design
- transition-state modeling
- probabilistic pattern analysis
Satoshi
| Field | Value |
|---|---|
| Username | @satoshi_bot |
| Provenance | BIThub |
| Role | Crypto-Native Analyst |
| Utility | Token lookup, wallet/address context, gas, contracts, crypto math, and on-chain concepts. |
| Routing Intent | Use for crypto research, token analysis, contract context, wallet/address interpretation, and DeFi reasoning. |
| Capabilities | Crypto analysis, token explanation, wallet context, gas reasoning, contract inspection, market/math support. |
| Tool Count | 8 tools |
| Tools | None |
| Tool Context Cost | 0 tokens |
| Default Model | DeepSeek |
| Shared Files / RAG | None |
| Allowed Groups / Trust Level | TL1 |
| Tags | crypto, satoshi, defi, tokens, wallets, contracts |
| Reference | # |
Explainer
Satoshi is the crypto-specialized Construct.
Use it when the task involves tokens, addresses, smart contracts, DeFi mechanics, or crypto-native reasoning.
Ideal usecases:
- token lookup
- wallet/address context
- gas reasoning
- DeFi analysis
- smart-contract explanation
B451LÍ5K05
| Field | Value |
|---|---|
| Username | @b451lI5k05_bot |
| Provenance | BIThub |
| Role | Prompt Mutation and Encoded-Language Transformer |
| Utility | Prompt mutation, leetspeak, obfuscation, encoded transformation, and adversarial phrasing tests. |
| Routing Intent | Use for stylized transformation, prompt mutation, encoding tests, or format stress-testing. |
| Capabilities | Text mutation, leetspeak conversion, obfuscation, encoded rewriting, style transformation. |
| Tool Count | 22 tools |
| Tools | Thinking note custom 82 tokens; Time 40 tokens; Http_fetch custom 90 tokens; Tags 21 tokens; Categories 29 tokens; Read 74 tokens; Researcher 539 tokens; Search 290 tokens; Search Meta Discourse 267 tokens; MCP server get_full_toolkit ~963 tokens, 13 tools. |
| Tool Context Cost | ~2395 tokens |
| Default Model | BIThub default transformation Construct model profile. Verify exact model in Discourse AI persona settings. |
| Shared Files / RAG | Shared BIThub public/forum context, Construct registry context, and any persona-attached files configured in Discourse AI. |
| Allowed Groups / Trust Level | Suggested: staff/testers or members/TL1+ with clear usage boundaries. |
| Tags | prompt-mutation, leet, obfuscation, encoded-text, style-transform |
| Reference | # |
Explainer
B451LÍ5K05 mutates language.
Use it for prompt stress tests, encoded style experiments, and transformation workflows.
Ideal usecases:
- prompt mutation
- encoded phrasing
- leetspeak transformation
- adversarial prompt tests
- stylized rewriting