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Fill a prompt

fill_prompt
Read-only

Fill a ContexteTech prompt template and return the ready-to-send text, nothing else. Use it when the user wants a prompt applied to their own case; call load_resource first if you need the template or the exact variable names. 'variables' maps each {{name}} of the template to its text value; extra keys are ignored. Fails with an error if the code is unknown, if the resource is not a prompt, or if a template variable is missing (the error lists the missing names).

Input Schema

NameRequiredDescriptionDefault
codeYesShort code of the prompt
variablesYesValues for each {{variable}}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description goes further by disclosing error behavior (unknown code, non-prompt resource, missing variable) and that missing-variable errors enumerate the missing names, which an agent can use to self-correct. It stops short of describing pagination/output format details, but the return contract is stated.

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?

Four tight sentences, front-loaded with purpose and output, then usage, then parameter semantics, then failure modes. No sentence is filler; each adds a distinct fact.

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

Completeness5/5

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

Covers purpose, when-to-use, the sibling alternative, variable semantics, and the full failure surface including error content. With 2 required params and no output schema, nothing an agent needs to invoke it correctly is missing.

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 the baseline is 3, but the description adds real meaning: variables map each {{name}} placeholder to its text value and extra keys are silently ignored. That is behavior the schema's generic 'Values for each {{variable}}' does not convey.

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?

States a specific verb and resource ('Fill a ContexteTech prompt template') plus the exact output ('ready-to-send text, nothing else'). It also names the sibling load_resource for a related need, so an agent can distinguish this tool from its neighbors without inspecting a schema.

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

Usage Guidelines5/5

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

Gives an explicit when-to-use condition ('when the user wants a prompt applied to their own case') and routes the agent to load_resource when it needs the template or exact variable names. Both the trigger and the alternative are stated, not 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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