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Ambuj123-lab

Ambuj Systems - Career Workspace

jd_analyzer

Read-onlyIdempotent

Extracts skills from a job description and matches each against your resume using actual evidence, returning STRONG_MATCH, PARTIAL_MATCH, TRANSFERABLE, or MISSING per skill.

Instructions

Evidence-backed JD matching. Extracts skills from JD, matches each against resume with ACTUAL evidence. Returns STRONG_MATCH / PARTIAL_MATCH / TRANSFERABLE / MISSING per skill.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jd_textYesFull job description text (max 10000 chars)
resume_textYesUser's resume/experience text (max 15000 chars)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real value by disclosing the result taxonomy (STRONG_MATCH / PARTIAL_MATCH / TRANSFERABLE / MISSING) and the evidence-backed matching behavior, though it says nothing about determinism, cost, or handling of empty/extreme input.

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 tight sentences with no filler, and the core purpose is front-loaded in the opening clause. The first sentence is slightly redundant with the second, which keeps it just short of ideal.

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?

With no output schema, the description is responsible for conveying return values, and it does so via the four match categories. Missing only secondary detail such as how evidence is surfaced per skill or what the agent should do with MISSING results, which keeps it from a 5.

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 description coverage is 100%, with both parameters documented including their character limits, so the schema does the heavy lifting. The description adds only an indirect mapping ('from JD' / 'against resume') and no format or syntax guidance beyond that, which is the baseline 3 case.

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?

Names a specific verb and resource: extracts skills from a JD and matches each against a resume, and it even names its output taxonomy. It's clear what the tool does, though it never explicitly separates itself from closely related siblings like evidence_validator or ats_readiness.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied — the two required inputs (jd_text, resume_text) make the scenario obvious, but there's no statement of when to reach for this tool versus cover_letter_generator or ats_readiness, nor any exclusions or prerequisites.

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