Skip to main content
Glama
andrewaws26

Claude Works

by andrewaws26

build_resume

Assemble a tailored one-page resume from verified experience fragments and run static quality gates to ensure completeness and accuracy.

Instructions

Build a tailored one-page resume from verified fragments and run the static gates.

Args: name: output file stem (becomes ".html" in the resumes dir). tagline: the header tagline (mid-level; no over-level words). summary: the summary paragraph. experience: list of [role_key, [bullet, ...]] where role_key is one of bnb / twinspires / upwork / humana / tesla / dojo / lifespring, and each bullet is a fragment NAME (e.g. "BNB_AI") or text tracing to CLAIMS_BANK. projects: list of project fragment names (e.g. "P_CASEK") or verified HTML. skills: list of [label, text] rows for the Skills block.

Returns the resume with lint_ok / verify_ok and any findings. The 1-page render gate runs separately via render_resume (it needs Chrome).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
skillsYes
summaryYes
taglineYes
projectsYes
experienceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description carries full burden. It describes that static gates run and returns lint_ok/verify_ok and findings, but doesn't elaborate on failure modes or what happens with invalid fragments. Adequate but not comprehensive.

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?

Reasonably concise with a clear front-loaded purpose sentence and a bullet list for parameters. Could be slightly more structured, but no wasteful sentences.

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?

Covers all 6 input parameters and mentions return values (lint_ok/verify_ok and findings). Notes that rendering is separate. Missing some context on static gates and error handling, but overall sufficient for a complex tool with output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description's Args section explains each parameter in detail, including constraints like valid role_keys and bullet formats. This adds significant meaning beyond the bare 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?

Clearly states the tool builds a tailored one-page resume from verified fragments and runs static gates. Distinguishes from siblings like render_resume by noting that the 1-page render is separate.

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?

Implicitly mentions that render_resume handles the 1-page render separately, but does not explicitly state when to use this tool versus verify_resume or other siblings. Lacks explicit when-to-use or when-not-to-use guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/andrewaws26/claude-works'

If you have feedback or need assistance with the MCP directory API, please join our Discord server