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elc-partnership-builder

by io.engineeringleaders
OverviewDiscussionsAdmin

How ELC company membership works + the two qualifying questions

get_partnership_options
Read-onlyIdempotent

START HERE for any company considering an ELC membership (personas: HR, CTO, employer branding). Returns how company membership works, real community reach figures, and the two qualifying questions with their valid answers. Companies only — individuals seeking a mentor for themselves get pointed to /mentor/ instead. After the visitor answers both questions, call match_package. Partner packages and tickets for the ELC Conference 2027 day are a separate offer with their own MCP server: https://mcp.elc-conference.io/mcp

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional. A short description of your goal and why you are calling this tool. Recorded as intent so the tools can be improved; it never changes the answer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"Optional. A short description of your goal and why you are calling this tool. Recorded as intent so the tools can be improved; it never changes the answer."
    • removedInput schema / required
      Removed value: -[
-  "context"
-]
  2. Changed2 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "context"
+]
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare this as a safe, idempotent, non-destructive, closed-world read, and the description respects that framing while adding useful behavioral context: it is the entry point of a multi-step flow and the next call is match_package. It does not describe pagination, latency, or caching, but for a static informational read tool that gap is minor.

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?

Front-loads the critical routing instruction ('START HERE') and each sentence carries distinct information: purpose, exclusions, next step, and sibling offer. It is slightly dense with parenthetical asides (personas, URL) but no sentence is wasted.

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

Completeness5/5

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

No output schema exists, but the description enumerates what is returned (membership mechanics, community reach figures, the two qualifying questions with valid answers) and where the flow continues. For a zero-required-parameter orientation tool, an agent has everything needed to call it and act on the result.

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?

There is a single optional parameter and schema coverage is 100%, so the schema already explains that context is optional intent-logging that never changes the answer. The description adds no additional parameter meaning, so the baseline of 3 for high schema coverage applies.

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?

Names a specific verb and resource ('START HERE' orientation tool returning how ELC company membership works, reach figures, and qualifying questions). It explicitly distinguishes itself from siblings by routing elsewhere: individuals to /mentor/, conference tickets to a separate MCP server, and post-qualification flow to match_package.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use it ('START HERE for any company considering an ELC membership'), its target personas, the exclusion ('Companies only — individuals seeking a mentor... get pointed to /mentor/'), and the sequencing into match_package. The alternative offers and their separate endpoint are named too, leaving nothing to inference.

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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