Four specialized AI agent skills available through the Model Context Protocol.
Tool | Skill | What It Does |
interpret_text | 8-lens hermeneutic analysis of any text or phenomenon | |
rune_reading | Elder Futhark divination with 14-layer interpretive stack | |
build_scenario | 15 foresight frameworks for rigorous hypothetical analysis | |
strategic_alignment_analysis | White Rock 6-phase protocol for short-term vs long-term misalignment detection |
Related MCP server: Tap
claw install darkd/integral-hermeneutics
claw install darkd/rune-wisdom
claw install darkd/what-if-scenario-builder
claw install darkd/strategical-alignmentAdd to your MCP client config:
{
"mcpServers": {
"darkd-skills": {
"url": "https://darkd.github.io/darkd-mcp/mcp.json"
}
}
}MIT-0
Construct rigorous, insightful what-if scenarios using 15 foresight frameworks including Shell Scenario Planning, Schwartz Eight-Step, Manoa Method, Causal Layered Analysis, Cross-Impact Analysis, Morphological Analysis, Pre-Mortem, Red Teaming, Base Rate Negation, Monte Carlo reasoning, Agent-Based reasoning, Backcasting, Wild Card analysis, Trend Impact analysis, and Intuitive Logics.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | The scenario topic or what-if question to explore | |
| framework | Yes | Which foresight framework to apply | |
| time_horizon | No | Time horizon for the scenario (e.g., 5 years, 2030, next decade) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose behavioral traits such as whether the tool is read-only, side effects, auth requirements, or output format. It only states what it does without any transparency beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose, but listing all 15 frameworks makes it somewhat verbose. However, it remains focused and actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and three parameters, the description does not explain return values, pagination, or any behavioral constraints. It is incomplete for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description redundantly lists the frameworks already present in the schema enum, adding minimal new meaning for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('construct') and the resource ('rigorous, insightful what-if scenarios'), and distinguishes itself from sibling tools like 'interpret_text' or 'strategic_alignment_analysis' by listing 15 specific foresight frameworks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for scenario building but does not provide explicit guidance on when to use this tool versus alternatives or when not to use it. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Analyze any text, statement, system, behavior, artifact, or phenomenon through 8 integrated hermeneutic lenses: literal, historical, structural, psychological, cultural, dialectical, meta-interpretive, and transformative. Use when interpreting, analyzing meaning, understanding perspectives, decoding messages, or performing deep reading.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text, statement, or phenomenon to interpret | |
| lens | Yes | Which hermeneutic lens to apply, or all for full multi-lens analysis | |
| context | No | Optional additional context about the text origin, author, or situation |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the 8 lenses but does not describe the output format, depth, or process, leaving gaps about what the agent can expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with efficient front-loading of the core purpose and usage guidance, every word earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and 3 parameters. The description fails to explain what the output looks like or the format of the analysis, which is critical for a complex analytical tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds limited value beyond listing the lens names. It does not elaborate on parameter semantics like the 'lens' enum values or the optional 'context' usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes text using 8 specific hermeneutic lenses, distinguishing it from sibling tools like build_scenario or rune_reading through its unique interpretative focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage scenarios such as interpreting, analyzing meaning, and decoding messages, but does not explicitly mention when not to use it or contrast with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Elder Futhark rune divination with 24 runes, 37+ spread layouts, and a 14-layer interpretive stack. Draws runes, provides traditional and modern meanings, and constructs layered interpretations including mythic, psychological, and practical dimensions.
| Name | Required | Description | Default |
|---|---|---|---|
| spread | Yes | The spread layout to use for the reading | |
| question | No | The question or situation to address with the reading | |
| depth | Yes | Interpretation depth: surface (basic meanings), deep (psychological/mythic layers), full (complete 14-layer stack) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses key behaviors: uses 24 runes, 37+ spreads, 14-layer stack, and outputs traditional/modern meanings. However, it omits details about randomness, state, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat verbose and includes the claim of '37+ spread layouts' while the enum only lists 8, which may mislead. It front-loads the core purpose but could be trimmed for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description should hint at return format; it only vaguely says 'provides meanings.' Also, the spread enumeration inconsistency reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the depth parameter (surface/deep/full) and the overall interpretive process, going beyond the schema's brief descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs Elder Futhark rune divination with specific rune count, spread layouts, and interpretive layers, distinguishing it from sibling tools like build_scenario or interpret_text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites, exclusions, or appropriate contexts for divination.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Detect where short-term optimization (profit, efficiency, convenience) is building long-term fragility, dead ends, or collapse. Uses the White Rock 6-phase protocol: (1) map current trajectory, (2) identify disruption signals, (3) premortem projection, (4) define long-term viability, (5) assess alignment gap across 9 dimensions, (6) map alternative trajectories. Works at interpersonal, organizational, and systemic scales.
| Name | Required | Description | Default |
|---|---|---|---|
| subject | Yes | The decision, strategy, trend, or behavior to analyze for alignment | |
| scale | Yes | Analysis scale: interpersonal (1-5 years), organizational (3-15 years), systemic (10-50+ years) | |
| focus_dimension | Yes | Which gap dimension to emphasize, or all for full 9-dimension assessment | |
| mode | Yes | prospective: analyze a current/future trajectory; retrospective: analyze a known past failure |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It details the 6-phase protocol and the three scales, providing good transparency about the tool's methodology. However, it does not mention output format or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using three sentences to state purpose, protocol, and scales. It is front-loaded with the core purpose. The protocol listing is slightly lengthy but informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 required parameters, no output schema), the description explains the process well but omits details about the output format or what the agent should expect after invoking it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented. The description adds value by explaining the timeframes associated with scale, the meaning of 'all' for focus_dimension, and the difference between prospective and retrospective modes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: detecting where short-term optimization builds long-term fragility. It distinguishes itself from siblings (build_scenario, interpret_text, rune_reading) by specifying a unique protocol and analytical focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (analyzing decisions/strategies for alignment). It does not explicitly state when not to use it or mention alternatives, but the context of sibling tools provides implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0build_scenariointerpret_textrune_readingstrategic_alignment_analysisEach tool has a unique, clearly defined purpose: scenario building, text interpretation, rune divination, and strategic alignment analysis. No overlap exists.
All names use snake_case, but 'build_scenario' and 'interpret_text' follow verb_noun while 'rune_reading' and 'strategic_alignment_analysis' are noun_noun, a minor inconsistency.
With 4 tools, each covering a distinct and complex domain (foresight, hermeneutics, rune divination, strategic analysis), the count is well-scoped.
The set covers foresight, interpretation, divination, and strategic analysis comprehensively within its esoteric domain. Minor lack of a general 'decision-making' tool is noted but not critical.
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If you are the server author, to access and configure the admin panel.
Divination for AI agents: Hafez, Tarot, I Ching, Runes, Geomancy, and the five-oracle Council.
AI agent for business strategy and business design — run strategy missions and 15 analyses.
AI agent infrastructure for discovery, authorization, execution, identity, and signed receipts.
Deterministic reasoning stack for AI agents: simulate, decide & compute, plus cross-domain tools.
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