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Glama

elc-trade

by io.engineeringleaders

Buy reach in the ELC community

buy_reach
Read-onlyIdempotent

Answers 'how do we get in front of 3,300+ CEE engineering leaders, and what does it cost?' Builds a cart from ELC's nine published one-off reach items — newsletter section, dedicated newsletter, hosted meetup, podcast episode, decision-maker dinner, community survey, demo session, LinkedIn post, job listing — applies the published combo discount, and returns a decision-ready quote a human can sign.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesExplain 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."
budget_eurNoOptional: what you have to spend. Does not change any price — the quote will say whether the cart fits and what to drop if it does not.
oneoff_idsNoRequired. Which one-off reach items to quote. One or more of: newsletter-section, newsletter-dedicated, meetup-hosted, podcast-episode, dinner, survey, demo-session, linkedin-post, job-listing. Combo discount applies automatically.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
reportYesThe full human-readable report.
sourceYesCanonical engineeringleaders.io page this answer derives from.
verdictNoHeadline verdict, when the tool returns one.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changed
    • changedInput schema / properties / oneoff_ids / description
      Previous value: -"Which one-off reach items to quote. One or more of: newsletter-section, newsletter-dedicated, meetup-hosted, podcast-episode, dinner, survey, demo-session, linkedin-post, job-listing. Combo discount applies automatically."New value: +"Required. Which one-off reach items to quote. One or more of: newsletter-section, newsletter-dedicated, meetup-hosted, podcast-episode, dinner, survey, demo-session, linkedin-post, job-listing. Combo discount applies automatically."
    • removedInput schema / properties / oneoff_ids / items / enum
      Removed value: -[
-  "newsletter-section",
-  "newsletter-dedicated",
-  "meetup-hosted",
-  "podcast-episode",
-  "dinner",
-  "survey",
-  "demo-session",
-  "linkedin-post",
-  "job-listing"
-]
    • removedInput schema / properties / oneoff_ids / minItems
      Removed value: -1
    • changedInput schema / required
      Previous value: -[
-  "oneoff_ids",
-  "context"
-]New value: +[
+  "context"
+]
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds valuable behavioral context beyond those: it builds a cart, applies a discount, and returns a quote a human can sign — making clear it does not actually execute a purchase despite the name 'buy_reach'. This prevents a potentially misleading interpretation.

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?

The description is two sentences with no filler. The user-facing question is front-loaded, and the second sentence packs in scope, item enumeration, discount behavior, and output format without wasted words. Every clause earns its place.

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?

With an output schema, annotations, and a 100% schema-described parameters, the description is mostly complete: it covers scope, items, discount logic, and the fact the output is a quote. The main gap is the unresolved oneoff_ids-required ambiguity and the lack of explicit routing against siblings, though those are relatively minor against an otherwise rich definition.

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 description coverage is 100%, so the schema already documents all parameters. The description adds a readable enumeration of the nine reach item types, which helps map labels to identifiers, but it does not add essential semantics beyond the schema. There is also an internal schema inconsistency: oneoff_ids is described as 'Required' in its property description but is absent from the top-level 'required' array, which could confuse an agent relying on the description.

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?

The description clearly states what the tool does: it builds a cart from ELC's nine published one-off reach items, applies the combo discount, and returns a decision-ready quote. The verb 'builds' and resource 'ELC's ... reach items' are specific, and the tool is easily distinguished from siblings like assess_community_launch_readiness or get_started.

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?

The description opens with the exact user question it answers: 'how do we get in front of 3,300+ CEE engineering leaders, and what does it cost?' This gives clear context for when to call it. However, it does not explicitly mention alternatives or when not to use it, though sibling names suggest these are distinct launch-readiness or partnership-evaluation tools.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most domain tools are cleanly separated: launch readiness, speaker readiness, topic evaluation, leadership benchmarking, partnership business case, and reach purchasing each map to a distinct workflow. The only real ambiguity is between get_started and get_more_tools, which both claim greeting/liveness/menu duties, so an agent might call the wrong one for those entry-point cases.

Naming Consistency4/5

Tool names are consistently imperative snake_case with clear verbs and objects (assess_*, benchmark_*, build_*, buy_*, evaluate_*). get_more_tools and get_started are slightly less resource-specific, and get_started is a phrasal verb rather than a strict verb_noun action, but the overall style is uniform.

Tool Count5/5

Eight tools is a well-scoped size for a community/partnership decision-support server. It is within the ideal range and each core workflow has its own tool without the set feeling bloated.

Completeness4/5

The set covers the main workflows: readiness checks, topic/speaker evaluation, leadership benchmarking, partnership business cases, and reach purchasing. It lacks operational follow-through like membership signup, event scheduling, or post-assessment action plans, but those are adjacent rather than core to the apparent purpose.

Resources