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Fill a prompt

fill_prompt
Read-only

Fill ContexteTech prompt templates by supplying a prompt code and values for {{variable}} placeholders, then get a ready-to-use prompt.

Instructions

Fill a ContexteTech prompt template ({{variable}} placeholders) and return the ready-to-use prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesShort code or author/name of the prompt
variablesYesValues for each {{variable}}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds that the operation performs placeholder substitution and yields a ready-to-use prompt, but says nothing about failure modes (unknown code, missing variable keys, extra variables).

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?

One tight sentence with the action, the input convention, and the return value front-loaded. Nothing is wasted, though it largely echoes the title 'Fill a prompt'.

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?

For a two-parameter, both-required tool with a nested variables object and no output schema, the description covers the transformation and the return value, which is the main gap. It still omits how the 'code' is resolved and what happens when variables don't match the template, leaving edge-case behavior undocumented.

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 coverage is 100% and the schema already defines both 'code' and the 'variables' map with its {{variable}} placeholder semantics. The description's '({{variable}} placeholders)' remark restates the schema rather than adding format or lookup detail, so the baseline 3 applies.

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?

States a specific verb (Fill) and resource (a ContexteTech prompt template with {{variable}} placeholders) plus the resulting artifact (ready-to-use prompt). It does not compare itself to the closest sibling, load_resource, which an agent might otherwise reach for when fetching a prompt.

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?

There is no explicit when-to-use statement, no prerequisite (e.g., where 'code' comes from), and no mention of alternatives such as load_resource. Usage is only weakly implied by the verb 'Fill'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.