social_statsFetch social media stats for a coin by CoinDesk Data (formerly CryptoCompare) coinId: Twitter followers, Reddit subscribers, Facebook likes, GitHub activity.
| Name | Required | Description | Default |
|---|---|---|---|
| coinId | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| Data | No | Social stats data |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "coinId": 1
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Social media statistics for a coin",
+ "properties": {
+ "Data": {
+ "description": "Social stats data",
+ "type": "object"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds minimal behavioral details beyond purpose; it does not mention potential errors, rate limits, or return format. It partially compensates by listing the data fields, but overall transparency is limited.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence without redundant words. It effectively conveys the essential information and lists key metrics, maintaining high conciseness and structural clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema provided, so the description must compensate. It lists the specific social media stats (Twitter followers, Reddit subscribers, Facebook likes, GitHub activity), giving an incomplete picture of the response. It does not mention other potential fields or the format of the output, leaving some context missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines coinId as a required number with no description. The description clarifies that it is a CoinDesk/CryptoCompare coinId and indicates the type of data returned, but does not explain the numeric format or origin thoroughly. This adds partial meaning but leaves ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Fetch social media stats for a coin' with a specific resource (social media stats) and target (a coin). It distinguishes from sibling tools by focusing exclusively on social metrics, unlike others like price or historical data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool compared to alternatives. While it mentions the coinId format, it does not provide context such as 'use when you need social engagement numbers' or differentiate from similar tools like all_coins or price. The description lacks practical usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tool families overlap heavily: ask_pipeworx, its beta, and grounded variants, the six polymarket_* tools, and the three price endpoints (price, price_full, price_multi) can be confused despite distinct purposes. Long descriptions provide some disambiguation, but an agent must read carefully to select the correct tool.
Tool names mostly follow snake_case with verb_noun or noun_noun patterns (all_coins, compare_entities, top_market_cap), and related families share clear prefixes (histo_*, polymarket_*). Minor deviations exist (bare verbs like remember/forget, brand names like ask_pipeworx), but the overall pattern is readable and consistent.
With 46 tools, the server is far beyond the 3-15 well-scoped range and nearly double the 25-tool threshold for 'too many'. Many tools are unrelated to the server's apparent crypto purpose (generate_llms_txt, scan_dependency, memory helpers), making it feel like a general-purpose utility rather than a focused data service.
The crypto data surface is fairly complete (spot, historical, top lists, news, social stats, exchange metadata), and the Pipeworx meta-tools (ask_pipeworx, deep_research, entity_profile) cover a broad range of factual queries. However, there are notable gaps: no direct way to fetch pipeworx:// citation URIs, and no advanced crypto order-book/trade endpoints, leaving some workflows as dead ends.