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linkedin-pilot

linkedin-pilot

by juanpacj-wq
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

linkedin_job_save

Save or remove a job posting from your LinkedIn saved list. Manage bookmarked jobs directly to organize your search.

Instructions

Guarda o quita una oferta de la lista de guardados.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job": "<job>"
    },
    "name": "linkedin_job_save"
  }
}

Input Schema

NameRequiredDescriptionDefault
jobYes
saveNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations exist, so the description carries the full behavioral burden. It does convey that the tool can both save and unsave, but it omits authentication requirements, whether the operation is idempotent, what happens on repeat calls, and how the target job is identified.

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?

A single short sentence, front-loaded with the core action and free of filler. It is efficient, though it is so terse that brevity comes at the cost of the missing detail noted elsewhere.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations, no output schema, and fully undocumented parameters, the description is too thin to let an agent call it correctly without guessing the `job` format and `save` semantics.

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

Parameters2/5

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

Schema description coverage is 0% and neither parameter is documented. The description hints that direction is controllable (save vs remove) but never explains what format the required `job` string takes (ID, URL, slug) or what the `save` boolean defaults to or does.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a clear verb pair ("Guarda o quita" = save or remove) and a specific resource (a job offer in the saved list), so an agent can tell it is not linkedin_job_apply or linkedin_my_jobs. It stops short of explicitly naming which sibling handles related operations, but the action is unambiguous.

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?

There is no statement of when to use this versus linkedin_job_detail, linkedin_job_apply, or linkedin_my_jobs, and no preconditions (login state, valid job identifier). Usage can only be inferred from the single sentence.

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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