Score how well a CV/resume matches a specific job posting. Fast and cheap — returns the original match score and the score after tailoring, plus requirement counts. Use this first to show the user the gap before a full tailor.
| Name | Required | Description | Default |
|---|---|---|---|
| cvText | Yes | The full CV/resume as plain text. | |
| jobDescription | Yes | The job posting text. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses performance (fast and cheap), return content (original and tailored scores, requirement counts), and implied non-destructive nature. With no annotations, description carries burden and does so adequately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with main action, highly efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains return values in absence of output schema, clarifies usage context. Could add note on expected input format (plain text) but sufficient overall.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions. The tool description adds no param-specific detail beyond stating it takes full CV and job posting as plain text, which is already in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it scores a CV against a job posting, specifies returned values, and distinguishes from sibling tool tailor_cv by noting usage order.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises using this tool first to identify gaps before tailoring, referencing the sibling tool tailor_cv for the full tailor.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct, non-overlapping purpose: score_cv for assessment and gap analysis, tailor_cv for actual rewriting. No ambiguity.
Both tools follow a consistent verb_noun pattern with underscores: score_cv and tailor_cv, making them predictable.
With only 2 tools, the server is minimal but still covers the core workflow of scoring and tailoring. Could potentially include a tool for resetting or managing CVs, but the count is appropriate for the narrow domain.
The tools cover the essential steps: assess the gap and then tailor. While there are no additional tools for viewing history or managing multiple CVs, the surface is sufficient for the stated purpose.