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Read interview prep

read_interview_prep

Review interview prep Q&A notes stored in a markdown file, optionally filtered by company. Read questions and answers to prepare for interviews, with a friendly message when notes aren't found.

Instructions

Read the interview-prep Q&A markdown file (Interview_Prep_QA.md) and return it as text. Pass an optional company to return just that company's section. Returns a friendly message (not an error) if the file doesn't exist yet or the company has no section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyNoReturn only this company's section (case-insensitive).
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses key behaviors: returns text, handles missing file or missing company section with a friendly message rather than an error. This is adequate for a simple read operation.

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?

Two sentences, front-loaded with the primary action, and every phrase adds value (file name, return format, optional filter, error handling). No wasted words.

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?

For a tool with one optional parameter and no output schema, the description is complete. It covers the file source, behavior with and without the filter, and error/friendly-message handling. No additional context is needed.

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% with a clear property description. The main description repeats the optional company filter but adds no new meaning beyond the schema. Baseline 3 is appropriate.

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 reads a specific file (Interview_Prep_QA.md) and returns it as text, with an optional company filter. This specific verb+resource+scope distinguishes it from generic read_document or read_text_file siblings.

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?

Provides clear context for when to use: to retrieve interview prep content, optionally filtered by company. No explicit exclusions or alternatives are named, but the specificity of the file and behavior makes the usage clear.

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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