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sales-intelligence-mcp

search_linkedin_jobs

Read-only

Search LinkedIn for public job postings matching a query.

Wraps nexgendata/linkedin-jobs-scraper. Returns job title, company, location, posted date, and description. Posted-within filter is a soft hint applied client-side via the LinkedIn search UI.

Args: query: Free-text job query (e.g. "senior python developer"). location: Optional location (e.g. "Berlin", "Remote"). posted_within_days: Soft recency filter (default 14, max 90).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
locationNo
posted_within_daysNo

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already provide readOnlyHint and openWorldHint. The description adds value by noting the scraper reliance, return fields, and the 'soft hint' nature of the posted_within_days filter.

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?

The description is concise, front-loaded with the main purpose, and uses a clear args list. Every sentence adds value with no redundancy.

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?

The description covers return fields, soft filter behavior, and dependency. For a read-only search tool with simple parameters, this is nearly complete; only missing mention of pagination or result limits.

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?

Input schema has 0% description coverage. The description explains each parameter's purpose (free-text query, optional location with examples, and soft recency filter with defaults/limits), compensating well.

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 the tool searches for public LinkedIn job postings with a specific verb+resource combination. It differentiates well from sibling tools (e.g., company profiles, leads, funding).

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?

The usage context is clear—searching for jobs—but there is no explicit guidance on when not to use this tool or which alternative to choose. Siblings are sufficiently distinct to avoid confusion.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct sales intelligence function: from company profiling, tech detection, hiring signals, to lead finding and enrichment. Even the two enrichment tools (enrich_company vs. aggregate_company_profile) are clearly differentiated by depth and features.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (e.g., aggregate_company_profile, detect_tech_stack, find_b2b_leads). No mixing of conventions or vague verbs.

Tool Count5/5

10 tools is well-scoped for a sales intelligence server, covering the full pipeline from prospecting to enrichment and signal detection. It's neither too sparse nor overwhelming.

Completeness5/5

The tool set covers end-to-end sales research: lead generation, company enrichment, tech stack detection, hiring signals, email finding, YC directory, job search, and funding tracking. No obvious gaps for the intended domain.

Resources