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woladi

sugestim

by woladi

build_metaphor

Construct a structurally-parallel metaphor story to resolve a stuck situation. Input actors, relations, stuck point, and desired resolution to generate an isomorphism map and narrative frames.

Instructions

OFFENSE (with shield). Given a problem structure — actors, relations, a stuck_point and a desired_resolution — returns the scaffold for a structurally-parallel, surface-different story: the metaphor-construction frames (structural isomorphism, surface displacement, nested/open loops, embedded suggestion, the 'My Friend John' technique, displaced resolution, transderivational search) plus an isomorphism map to fill, a loop_stack sized to nesting_depth, and the output_contract. DEFENSIVE READ (always): a story whose structure mirrors your exact situation is inviting you to import its resolution — ask whether the parallel actually holds or just feels apt. direction:'offense'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorsYesActors in the real situation (e.g. 'client', 'the deadline'). The isomorphism map mirrors each.
relationsYesRelations between actors (e.g. 'client fears the deadline').
stuck_pointYesThe impasse the metaphor must structurally reproduce.
desired_resolutionYesThe resolution the story should arrive at.
nesting_depthNoOptional number of nested loops (e.g. '2', '3'). Default '2'.
langNoLanguage view of the response: 'pl', 'en', or 'both' (default).both
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It details the output components (frames, isomorphism map, loop_stack, output_contract) and includes a cautionary note about defensive reading. No mention of side effects or permissions, but sufficient for a generative tool.

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 information-dense but front-loaded with the core action. Each sentence adds value, though the list of frames could be more structured. Appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description adequately explains the return values and includes a defensive note. It covers the tool's complexity, though some terms like 'output_contract' could be expanded.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All parameters have schema descriptions (100% coverage), and the description repeats the parameter names but adds no extra meaning or usage guidance beyond the schema. Baseline score applies.

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: given a problem structure, it returns a metaphor scaffold with specific components. It distinguishes from sibling tools by focusing on metaphor construction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a 'DEFENSIVE READ' warning about when to question the metaphor's applicability, but does not explicitly state when to use this tool over siblings like 'analyze' or 'generate'. Usage context is somewhat implied.

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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