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skivuha

federal-compass-mcp

by skivuha

extract_ksa

Extract KSA requirements from federal job postings, categorize them by type, and optionally compare against your saved CV for qualification analysis.

Instructions

Extract KSA (Knowledge, Skills, Abilities) requirements from a federal job posting. Categorizes requirements by type (knowledge, skill, ability, experience, education, certification, other) and optionally matches them against your saved CV.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID (MatchedObjectId from search results)
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It discloses extraction, categorization, and optional CV matching, but does not mention whether the tool modifies data, required authentication, rate limits, or what happens if the CV is not saved. The output format and potential limitations are also not addressed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, approximately 20 words, with no redundancy. The main action and key features are front-loaded and clearly communicated without wasted words.

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?

Given the tool's simplicity (single parameter, no output schema), the description is mostly complete. It covers the core functionality and optional CV matching. However, it could be more complete by briefly noting that the output is a structured list or that the CV must be saved first. The lack of output schema explanation is acceptable as per rules.

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?

The schema covers 100% of the single parameter (job_id) with a description. The tool description does not add any additional meaning beyond the schema's 'Job ID (MatchedObjectId from search results)', so it meets the baseline for high schema coverage.

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 clearly states it extracts KSA requirements from a federal job posting and categorizes them by type, with optional CV matching. The verb 'extract' and resource 'KSA from job posting' are specific. It distinguishes from sibling tools like get_job_details or check_qualification by focusing on categorization and CV matching.

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?

Implied usage: to extract structured KSA requirements after searching for a job, and optionally match against a saved CV. However, no explicit guidance on when to use this versus alternatives like check_qualification or compare_jobs, nor scenarios where CV matching is appropriate.

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

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