Incremental world state update — only what changed since a timestamp. ~30-50 tokens vs 800 for full state. For periodic refresh during long tasks.
| Name | Required | Description | Default |
|---|---|---|---|
| since | Yes | Relative (30m, 1h, 6h, 24h) or ISO timestamp | |
| format | No | Output format | markdown |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It mentions the incremental nature and token efficiency (~30-50 vs 800), which is useful. However, it does not disclose whether the operation is read-only, what happens when no changes exist, or the response structure beyond the format parameter in the schema. It provides some context but not comprehensive behavioral disclosure.
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 exceptionally concise, consisting of three short clauses that immediately establish purpose, efficiency, and use case. Every word earns its place, and it is properly front-loaded with the core concept.
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 a simple 2-parameter tool with no output schema, the description covers purpose, usage, and efficiency. The format parameter (markdown/json) gives some hint about return structure, but the description does not mention potential responses when there are no changes or clarify the exact content. Still, it is largely complete for the tool's simplicity.
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 100% for both parameters ('since' and 'format'). The description only repeats the 'since a timestamp' idea from the schema and adds no additional meaning about parameter syntax, default behavior, or dependencies. Baseline 3 is appropriate.
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 provides an incremental world state update, explicitly framing it as a delta since a timestamp. This distinguishes it from siblings like get_world_state and other delta tools. The verb 'update' is slightly off (it retrieves an update), but the meaning is 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 description provides a clear usage context: 'For periodic refresh during long tasks.' It also implies an alternative by comparing token counts to 'full state,' but does not explicitly name a tool like get_world_state. This makes the guidance clear but not fully explicit.
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.
Many tools have overlapping purposes, such as multiple market query tools (scan_markets, screen_markets, get_market_detail, get_market_diff, get_market_history, inspect_ticker) and legislative tools (legislation, get_legislation, list_legislation, query_gov). Aliases like get_heartbeat_config/get_heartbeat_status and explore_public/explore_theses add further confusion. An agent would struggle to select the correct tool without deeply reading each description.
Most tools follow a verb_noun pattern (get_, list_, create_, update_), but there are notable deviations: 'legislation' lacks the 'get_' prefix, 'stt' and 'tts' are acronyms, 'monitor_the_situation' is a full phrase, and 'x_account/x_news/x_volume' use a non-standard prefix. The overall style is readable, but the mixed conventions reduce predictability.
108 tools is extreme for any server, even one covering prediction markets, trading, portfolio management, forum, skills, and speech. The massive surface area overwhelms agents and makes the server feel more like a platform than a coherent toolkit. This many tools inevitably leads to redundancy and maintenance burden.
The server covers an impressively broad domain: market data, thesis management, intents, strategies, positions, portfolio, forum, skills, legislative and economic queries, and audio/visual processing. Minor gaps exist (e.g., no delete for skills/theses, no update for some portfolio items) but core workflows are well-supported. Overall lifecycle coverage for most entities is strong.
