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Vishu-ak

resumeforge

by Vishu-ak

Build the application kit

build_application_kit

Generate a complete application kit from a job description and tailored resume: checklist, auto-reject check, form answers, cover letter, recruiter messages, interview prep, and tracker entry.

Instructions

Everything needed to actually apply, generated from the JD and the candidate's materials: an apply-today checklist with portal-specific tips (Workday, Greenhouse, Lever…), an auto-reject check (years, degree, sponsorship, location, must-haves), copy-paste answers to application form questions (including honest 'years with X' computed from role dates), a cover letter, referral and recruiter messages with LinkedIn search links, a LinkedIn connection note, follow-up and thank-you emails, LinkedIn headline/About/skills updates, interview prep (elevator pitch, likely questions, 'defend every bullet'), and a tracker entry. Call it after render_resume, passing the final resume.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
postedNoWhen it was posted, e.g. '3 days ago' or '2026-09-20'
resumeNoThe final tailored resume (strongly recommended)
companyNoCompany name, if known
jd_textYesFull job description text, including requirements and responsibilities
job_urlNoPosting URL. Used to detect the application portal and tailor tips.
candidateYes
job_titleNoExact job title, if known (improves title matching)
output_dirNo
save_filesNoLocal mode: save Application_Pack.md and Cover_Letter.docx next to the resume
log_applicationNoAppend to applications.csv. Set true only after the candidate confirms they submitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

The description adds behavioral context beyond the sparse annotations, notably that 'years with X' answers are computed honestly from role dates and that portal-specific tips depend on the application portal. It aligns with readOnlyHint=false by describing a content-generation operation, but it does not disclose file-output or logging side effects such as save_files or applications.csv.

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?

The description is information-dense, front-loads the purpose with 'Everything needed to actually apply,' and ends with a crisp sequencing instruction. It is a single long run-on that would be easier to scan as bullets, but every clause carries useful content and there is minimal filler.

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?

Because there is no output schema, the description carries the burden of explaining what the agent gets, and it lists the major artifacts clearly. It also covers the main input source and the required sequencing. Remaining gaps like save_files and log_application behavior are delegated to the schema rather than described, which is acceptable but not exhaustive.

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?

With 80% schema coverage, the schema already documents most parameters, and the description adds real meaning on top: the resume is framed as the output from render_resume, job_url implicitly matters for portal-specific tips, and the honest-years note explains how role dates in the resume feed generated answers. It does not enrich every parameter, but it goes well beyond restating the schema.

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 names a specific action and resource: building the application kit from the JD and candidate materials. It enumerates concrete deliverables (checklist, auto-reject check, cover letter, messages, interview prep, tracker entry) and distinguishes the tool from upstream siblings like analyze_job_description and render_resume by framing it as the final packaging step.

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?

It gives an explicit workflow instruction: 'Call it after render_resume, passing the final resume,' which tells the agent when to invoke the tool and what input to provide. It does not spell out when not to use it or compare against sibling tools beyond that sequencing note, so it falls just short of full usage guidance.

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