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Add Target Company

add_target_company

Add a company to your MBA job-search target list, specifying priority and its careers URL to auto-detect the job board (Greenhouse, Lever, or Ashby) for live job tracking.

Instructions

Add a company to the target list.

Paste the company's careers or job-board URL as ats_url and the board is resolved automatically (Greenhouse, Lever or Ashby). Without one, job search for this company falls back to Adzuna if it is configured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCompany name as you'd say it, e.g. "Bain & Company".
ats_urlNoCareers/job-board URL, e.g. https://boards.greenhouse.io/acme
priorityNo1 = dream firm, 2 = core target, 3 = stretch/backup.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations present, the description carries the behavioral burden. It usefully discloses two non-obvious behaviors: automatic ATS board resolution and fallback to Adzuna when no URL is provided. It does not mention duplicate handling, required permissions, or side effects beyond the fallback search.

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?

Three short sentences with no filler: the first states the core operation, the second explains URL resolution, and the third covers the no-URL fallback. The description is front-loaded and every sentence contributes.

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

Completeness4/5

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

The schema documents all parameters and an output schema exists, so return-value details are not needed. The description covers the main call behavior and the important fallback, but leaves duplicate/update behavior unstated; for a mutation tool without annotations that is a minor gap.

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?

Since schema coverage is 100%, the baseline is 3, but the description adds real value by explaining ats_url: it is auto-resolved to a supported ATS, and omitting it changes job-search behavior. The priority and name parameters remain documented only by the schema, which is acceptable.

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 opens with a specific action and object: 'Add a company to the target list', clearly distinguishing this from pack-level operations like add_target_pack. It could more explicitly contrast with sibling tools, but the verb/resource pair is unambiguous.

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 gives no guidance on when to choose this tool over sibling tools or when an alternative is preferred. It explains conditional behavior around ats_url, but that is a runtime fallback, not tool-selection guidance.

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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