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interview_prep

Prepare for a job interview using only what you can honestly back up from your CV. Fetches the saved job post and maps each keyword to your evidence, stories, and honest standing.

Instructions

Prepare the interview for one logged application from what the person can honestly back up. Call it first with only application to get the saved job post (post_text), then again with the post's keywords. For each keyword it returns their level, evidence, stories (the bullets that show it, those in the CV they sent first) and a standing: strong (tell a story from those bullets), no_achievement (ask for a real example), marked_pending (ask for evidence), familiarity (say it is familiarity) or lacking (say so honestly). Every story must come from stories. With notes, saves the approved prep to /prep/.md.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoThe prep notes the person approved, in Markdown. Saved to <profile>/prep/<application>.md, replacing earlier notes.
profileNoPath of the profile folder. Leave it out to use the server's default (--profile or HONEST_CV_PROFILE).
keywordsNoRequired keywords from the job post, in its own wording. Leave out on the first call to get the saved post's text.
preferredNoNice-to-have keywords from the job post.
applicationYesApplication id, from list_applications.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.2

TDQS

A4.6/5.0
Behavior4/5

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

With annotations declaring readOnlyHint=false and destructiveHint=false, the description adds real behavioral context: the write path persists to <profile>/prep/<id>.md and 'replacing earlier notes', disclosing an overwrite that the annotations don't surface. It stops short of permission/auth or failure behavior, so 4 rather than 5.

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?

Front-loaded with the purpose and then the call sequence, and nearly every clause adds operational detail. It is dense and slightly run-on ('those in the CV they sent first'), but there is little dead weight.

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 5-parameter tool with no output schema, the description covers the whole cycle: inputs per call, the returned fields (level, evidence, stories, standing), the enumerated standing meanings, and the persistence side effect. Nothing essential is left for the agent to guess.

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 operative meaning the schema cannot: `keywords` must be in the post's own wording and pulled from the first call's `post_text`, and `notes` is what the person approved. It explains how keywords/preferred drive the returned keyword breakdown rather than just restating them.

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 ('prepare the interview for one logged application') and frames the scope as grounding prep in what the candidate can honestly back up. No sibling tool does interview prep, so the agent can distinguish it immediately.

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 two-call protocol: first with only `application` to retrieve the saved post, then again with the post's keywords, plus the optional `notes` path for saving. It also prescribes what to say aloud for each `standing` value, which is genuine when/how guidance.

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