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Glama

linkedin_profile_edit

Fill in a specific LinkedIn profile section using visible field labels, with saving optional so you can review the form before making changes public.

Instructions

Rellena una sección del perfil y opcionalmente la guarda. Los campos se identifican por su etiqueta visible (admite coincidencia parcial). Con save=false deja el formulario abierto y relleno para que lo revises: es lo recomendado la primera vez.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
saveNotrue para guardar. Por defecto false (solo rellena).
valuesYesEtiqueta → valor. Ejemplo: {"Cargo": "Ingeniero de datos", "Empresa": "ACME"}
sectionYesUna de: intro, about, experience, education, skill, certification, project, language, course, honor, publication, organization, patent, contactInfo, openToWork

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden, and it contributes one genuinely useful trait: save=false leaves the form open and filled for review, plus partial label matching. It omits other important mutation behavior such as auth requirements, whether save=true overwrites existing content, or failure handling.

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?

Three short sentences, front-loaded with the purpose, followed by the label-matching rule and the save recommendation. Every sentence adds distinct information with no filler.

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

Completeness3/5

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

For a mutation tool with a nested object and no output schema, the description explains the fill-vs-save model but omits what happens after a successful save (navigation, confirmation, errors). The rich schema compensates partially, but the behavioral picture is not fully closed.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema: keys of the values object resolve by visible label and support partial matching, and the save=false behavior is spelled out as a review flow. This is useful semantics not captured in the field descriptions alone.

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?

States a specific verb+resource: 'Rellena una sección del perfil y opcionalmente la guarda', which clearly conveys a profile-section write. It does not, however, differentiate itself from overlapping siblings like linkedin_profile_headline or linkedin_profile_about, so the agent cannot tell when to prefer this generic editor.

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?

Gives a concrete recommended workflow: 'Con save=false ... es lo recomendado la primera vez', which tells the agent how to sequence a first invocation safely. It does not, however, address when to use this tool versus the dedicated sibling editors, so the selection guidance is incomplete.

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