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mcp-lightcast

mcp-lightcast

by lawwu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Bulk Retrieve Skills

bulk_retrieve_skills
Read-onlyIdempotent

Retrieve multiple skills from Lightcast in a single request by passing skill IDs, reducing the need for separate calls.

Instructions

Retrieve multiple skills in one request.

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": {
      "skill_ids": "<skill_ids>"
    },
    "name": "bulk_retrieve_skills"
  }
}

Input Schema

NameRequiredDescriptionDefault
versionNolatest
skill_idsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world behavior, so the safety profile is covered. The only added context is 'in one request', implying batching efficiency; nothing is said about partial failures, unknown IDs, ordering of results, or payload size tradeoffs.

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 with zero filler and the batching intent front-loaded. Its brevity is efficient, though the same brevity is the source of the specification gaps penalized 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?

An output schema exists, so return values need no explanation, but for a bulk lookup accepting up to 1000 IDs the description omits essential behavior such as handling of invalid or missing IDs and what the response contains per item. Two undocumented parameters and no usage context leave it thin for this complexity.

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%, so the description carries the burden, yet it never mentions the required skill_ids array or the optional version field and its 'latest' default. 'Multiple' only faintly hints at a list input, leaving both parameters effectively undocumented in prose.

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 and resource ('Retrieve ... skills') plus the batching qualifier 'multiple ... in one request', which distinguishes it from single-skill retrieval siblings. It does not name a sibling explicitly, so it stops short of full differentiation.

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 guidance on when to choose this tool over search_skills, get_skill_details, or get_skills_metadata, and no mention of the practical limits (up to 1000 IDs) or when batching is preferred over repeated single calls.

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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