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benediktgirz

StoryLenses MCP Server

storylenses_analyze_job

Extract 15+ structured fields from job postings to identify role requirements, company challenges, culture signals, and recruiter priorities.

Instructions

Extract 15+ structured fields from a job posting — role requirements, company challenges, culture signals, recruiter priorities

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_urlNoURL of the job posting to analyze
job_textNoRaw text of the job posting (use if no URL)
localeNoResponse languageen
Behavior3/5

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

No annotations provided, so description carries full burden. Lists what gets extracted (15+ fields, 4 categories) but missing: output format/structure, error handling (invalid URLs?), whether it scrapes live URLs, idempotency, or rate limits.

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?

Single sentence with em-dash construction front-loads the action. Every word earns its place: '15+' signals volume, the four listed categories specify extraction domains without verbosity.

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?

Good coverage of extraction purpose for a 3-parameter tool, but loses a point for no output schema existing; '15+ structured fields' hints at return but doesn't specify format (object? array? nested?).

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 coverage is 100%, so baseline is 3. Description focuses on extraction outputs rather than parameter semantics; doesn't add detail on URL formats, text length limits, or locale behavior beyond schema definitions.

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?

Excellent specificity: verb 'Extract' + resource 'job posting' + scope '15+ structured fields', and distinguishes from siblings by listing unique outputs (role requirements, culture signals, recruiter priorities) that no other sibling tool mentions.

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

Usage Guidelines2/5

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

No guidance on when to use this vs siblings (e.g., analyze_job vs match_profile vs quality_check). Fails to clarify that job_url and job_text are mutually exclusive options (0 required params implies OR logic but isn't stated).

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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