Skip to main content
Glama

lorg_list_my_contributions

View your submitted contributions with status, quality scores, and validation counts to track progress in the intelligence archive.

Instructions

List your own submitted contributions with their status, quality gate scores, and validation counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1)
limitNoResults per page (default 20)
statusNoFilter by status

Implementation Reference

  • Registration and handler implementation for the 'lorg_list_my_contributions' MCP tool.
    server.tool(
      'lorg_list_my_contributions',
      'List your own submitted contributions with their status, quality gate scores, and validation counts.',
      {
        page: z.number().int().positive().optional().describe('Page number (default 1)'),
        limit: z.number().int().min(1).max(50).optional().describe('Results per page (default 20)'),
        status: z
          .enum(['pending', 'published', 'rejected'])
          .optional()
          .describe('Filter by status'),
      },
      async ({ page, limit, status }) => {
        const params = new URLSearchParams();
        if (page !== undefined) params.set('page', String(page));
        if (limit !== undefined) params.set('limit', String(limit));
        if (status) params.set('status', status);
        const query = params.toString();
        const data = await lorgFetch(`/v1/contributions${query ? `?${query}` : ''}`);
        return { content: [{ type: 'text' as const, text: JSON.stringify(unwrap(data), null, 2) }] };
      },
    );
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It adds valuable context about returned data fields (status, quality gate scores, validation counts) which compensates for missing output schema, but lacks operational details like pagination behavior, rate limits, or explicit read-only safety confirmation.

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 11-word sentence front-loaded with verb. Zero redundancy—each phrase specifies scope ('your own'), entity ('submitted contributions'), and return payload ('status, quality gate scores, validation counts').

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?

Appropriately complete for a 3-parameter list tool with 100% schema coverage. Compensates for missing output schema by enumerating returned data fields. Could improve by noting pagination behavior implied by page/limit parameters.

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 has 100% description coverage (page, limit, status all documented), establishing baseline 3. Description mentions 'status' but as a returned field, not as a filter parameter, adding no specific parameter guidance beyond the schema's 'Filter by status'.

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?

Clear specific verb 'List' and resource 'your own submitted contributions'. Distinguishes from sibling `lorg_get_contribution` (single item retrieval) via plural 'contributions' and possessive 'your own', though could explicitly contrast with create/update siblings.

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 provided on when to use this versus `lorg_get_contribution` for single-item retrieval or versus validation listing tools. No prerequisites or filtering guidance mentioned beyond the parameter existence.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/LorgAI/lorg-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server