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chrbailey

promptspeak-mcp-server

ps_symbol_import

Import symbols in bulk from external sources like HuggingFace, JSON, or CSV to categorize and structure data for AI agent governance.

Instructions

Bulk import symbols from external data (HuggingFace, JSON, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesData source format
dataYesThe data to import (format depends on source)
categoryYesCategory for imported symbols
id_prefixYesPrefix for generated symbol IDs (e.g., Ξ.Q.DEEPSEARCHQA)
transformNoField mapping from source data to symbol fields
defaultsNoDefault values for fields not in source data
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. 'Bulk import' implies a write/mutation operation, but it doesn't disclose critical traits: whether it overwrites existing symbols, requires specific permissions, has rate limits, returns success/failure counts, or handles errors. For a complex import tool with 6 parameters, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action ('bulk import symbols') and includes relevant examples. Every word earns its place, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (6 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't address behavioral aspects like mutation effects, error handling, or return values. For a bulk import operation that likely modifies system state, more context is needed to use it safely and effectively.

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?

Schema description coverage is 100%, so the schema already documents all parameters well. The description adds marginal value by hinting at external sources (HuggingFace, JSON, etc.), which aligns with the 'source' enum, but doesn't explain parameter interactions (e.g., how 'transform' maps to 'data'). Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('bulk import') and resource ('symbols from external data'), with specific examples of sources (HuggingFace, JSON, etc.). It distinguishes from sibling tools like ps_symbol_create (single creation) and ps_config_import (configuration import), though not explicitly named. It loses a point for not explicitly differentiating from siblings like ps_symbol_add_alternative or ps_symbol_update.

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

Usage Guidelines2/5

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. It doesn't mention prerequisites (e.g., data format requirements), when to choose this over ps_symbol_create for single symbols, or how it differs from ps_config_import. The agent must infer usage from the name and parameters alone.

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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