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strategic_alignment_analysis

Analyze decisions or strategies to detect where short-term gains create long-term fragility. Uses a 6-phase protocol to assess alignment gaps across 9 dimensions at interpersonal, organizational, or systemic scales.

Instructions

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subjectYesThe decision, strategy, trend, or behavior to analyze for alignment
scaleYesAnalysis scale: interpersonal (1-5 years), organizational (3-15 years), systemic (10-50+ years)
focus_dimensionYesWhich gap dimension to emphasize, or all for full 9-dimension assessment
modeYesprospective: analyze a current/future trajectory; retrospective: analyze a known past failure
Behavior4/5

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.

Conciseness4/5

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.

Completeness3/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

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