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list_applications

Retrieve read-only application registry entries filtered by portal or company, so you can verify prior applications before logging a new one.

Instructions

Read-only — never modifies the registry file. Returns rows from your application registry, optionally filtered by portal (exact, case-insensitive section heading) and/or company (case-insensitive substring match). Call this before log_application to check whether you've already applied to a company — the registry's own '## ' structure and column layout are returned as-is via each entry's fields dict, so this also works against registries with custom/non-English column names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
portalNoExact portal section name, e.g. 'justjoin.it'. Omit for all.
companyNoCase-insensitive substring match on the company field.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it declares the operation is read-only and never modifies the registry file, and explains how results are shaped ('returned as-is via each entry's fields dict') and that custom/non-English column names still work. It doesn't cover failure modes or empty-result behavior, keeping it out of the top tier.

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?

Three sentences, each doing work, with the safety constraint and the primary routing hint placed first. The trailing clause about custom/non-English column names is somewhat dense and could be tightened, but nothing is filler.

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?

An output schema exists, so return values needn't be spelled out, and the description still sketches the entry shape via the `fields` dict. For a two-optional-param read tool, an agent has everything it needs to select and invoke it correctly.

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 value by characterizing the filters as combining with 'and/or' and by clarifying that portal is an exact case-insensitive section heading rather than a fuzzy match. The company substring semantics largely restate the schema, so the addition is incremental rather than substantial.

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+resource ('Returns rows from your application registry') plus the filtering scope, which is enough to separate it from siblings like search_jobs and log_application without opening a schema. The read-only claim is front-loaded and unambiguous.

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?

Gives an explicit pre-call condition — 'Call this before log_application to check whether you've already applied to a company' — which names the sibling and the situation that selects this tool. It lacks any negative guidance (e.g. when search_jobs is the better choice), so it stops short of a full when/when-not treatment.

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