get_mindshare_coin[DRILL-DOWN] One coin's mindshare: its attention share %, rank, and velocity vs the prior window (rising/falling/stable/emerging). Same data as REST /mindshare/{coin}.
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes | ||
| rank | No | ||
| trend | No | ||
| velocity | No | ||
| disclaimer | No | ||
| mindshare_pct | No | ||
| sufficient_data | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safe read nature is known. The description adds behavioral context by specifying the exact metrics (attention share %, rank, velocity) and the categorical outcome (rising/falling/stable/emerging), which is useful for setting expectations. No contradiction with annotations.
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, efficient sentence that front-loads the drill-down nature and lists the core data points. Every word adds value; there is no redundancy or filler.
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?
Given the tool's simplicity (one parameter, output schema exists, annotations cover safety), the description covers the essential behavior and return content well. The only gap is the lack of parameter format guidance, but the overall picture is reasonably complete for an agent to select and invoke the tool.
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 sole parameter 'coin' has 0% schema description coverage. The description says 'One coin's mindshare' but doesn't specify whether 'coin' is a symbol, name, or ID, nor what format is expected. The REST endpoint reference hints at the parameter but doesn't define it. This is insufficient for a low-coverage parameter.
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: retrieving a single coin's mindshare data including attention share %, rank, and velocity vs prior window. The '[DRILL-DOWN]' tag and 'One coin's mindshare' distinguish it from the sibling tool 'get_mindshare', making the scope unambiguous.
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?
The '[DRILL-DOWN]' label and focus on a single coin imply this is the tool for per-coin mindshare details, while 'get_mindshare' likely handles broader overviews. However, it doesn't explicitly state when to use this versus alternatives or provide exclusions, so it's clear but not fully prescriptive.
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.
Most tools have clearly distinct purposes with detailed descriptions, but there are clusters of similar concepts (e.g., get_liquidity_map vs get_liquidation_map, get_state vs get_state_brief, multiple signal-related tools) that could cause misselection despite thorough documentation.
All tools follow a consistent lowercase verb_noun pattern, predominantly get_* nouns, with only a few non-get verbs like list_signals, rank_trades, log_trade, etc., but the style is uniform.
With 52 tools, the surface is extremely heavy for an agent to navigate. While the server's scope is broad, the count far exceeds the typical 3-15 range and falls into the 'too many' category.
The tool set covers the full lifecycle for journaling, signals, market analysis, and proof, with no major dead ends. Minor gaps exist, such as no dedicated get_trade_by_id (workaround via get_journal) and no get_market_state tool despite being referenced in get_state.