[marketsummary] What is heating up or cooling down — source-INDEPENDENT attention (mention velocity, 24h vs 7d baseline). Free = top 3 rising tickers; premium = the full rising/cooling ranking with velocity. Our attention signal does not depend on any single platform's API. Sparse data → coarse. Not advice.
| Name | Required | Description | Default |
|---|---|---|---|
| payment | No | ||
| session_token | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the data basis (mention velocity, 24h vs 7d), the independence from platform APIs, access tiers (free vs premium), data sparsity effects ('Sparse data → coarse'), and a disclaimer ('Not advice'). This provides meaningful behavioral context beyond basic read-only implications.
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 compact three sentences that front-load the core purpose and then efficiently covers limitations, access tiers, and data dependence. Every sentence adds value with 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?
The description provides a good high-level understanding of the tool's function and limitations, but it omits essential invocation details: the exact payment syntax for free vs premium, the role of session_token, and the output structure. Given the lack of an output schema and 0% parameter documentation, the description should be more complete to enable correct tool use.
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?
Schema description coverage is 0%, so the description must explain parameters. It explains the effect of 'payment' (free vs premium) but does not specify expected values or format. 'session_token' is completely unaddressed, leaving a critical gap for correct invocation. The description adds some semantic value but falls short of compensating for the lack of schema documentation.
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 identifies heating/cooling attention shifts using source-independent mention velocity with a 24h vs 7d baseline. It differentiates from siblings by explicitly noting the signal is not platform-specific, which distinguishes it from related tools like get_trending and get_buzz_score.
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 description implies usage through the source-independence claim and free/premium tier breakdown, but it never explicitly states when to use this tool over alternatives or names any sibling tool as a suggested substitute. The guidance is contextual rather than comparative.
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.
Each tool targets a distinct metric or action: attention shifts, buzz score, trending, and narrative tracking measure different facets; longs, shorts, and setups use different strategies; market regime, breadth, and summary are clearly separated. No two tools appear to produce the same output.
All tools follow a consistent pattern: a subsystem prefix (marketsummary__, tokensafety__, verify__) followed by an imperative verb_noun in snake_case. Verbs are predictable (get, find, track, ask, check, request, verify) and objects are clear, making the naming highly uniform.
24 tools is above the typical 3-15 range, but the server covers a broad market-intelligence domain with distinct feature areas. The tools are namespaced by subsystem, which helps agents navigate, but the volume still adds selection overhead.
The set covers market analysis, trending, sentiment, trade setups, token safety, and wallet verification for premium access. Minor gaps exist (e.g., no direct price/OHLC tool or token search), but agents can work around them using the provided tools.