Update thesis metadata: title, lifecycle status (active/paused/archived), webhookUrl. Use configure_heartbeat.paused for runtime heartbeat pause/resume.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | New thesis title | |
| apiKey | Yes | SimpleFunctions API key. Get one at https://simplefunctions.dev/dashboard/keys | |
| status | No | New status: active, paused, archived | |
| thesisId | Yes | Thesis ID | |
| webhookUrl | No | Webhook URL for confidence change notifications (HTTPS only) |
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?
No annotations are provided, so the description carries the full burden. It discloses that this is an update operation (mutation) and lists the mutable fields, which is useful. The extra sentence about configure_heartbeat.paused reveals a boundary of behavior. However, it doesn't disclose whether updates are partial or full replacement, what happens to existing values, or any side effects. This is comparable to the update_drive example, but with a bit more contextual detail, so a 3 is appropriate.
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 two sentences, front-loaded with the primary purpose and field list. The second sentence is a valuable disambiguation that prevents misuse. Every word earns its place, with no waste or redundancy. This is a model of concise, structured description.
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?
For a metadata update tool with 5 parameters, the schema covers all parameter semantics, and the description adds the key contextual disambiguation against configure_heartbeat. There is no output schema, but return values are not essential for this tool type. The main gap is no mention of auth requirements, but that's in the schema. Overall, it's complete enough for the agent to select and invoke correctly in most contexts.
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 coverage is 100%, and each parameter already has a clear description in the schema. The tool description groups fields ('title, lifecycle status, webhookUrl') and uses the term 'lifecycle status', which adds mild semantic framing. The clarification about configure_heartbeat for pause/resume provides context for the 'status' parameter, but overall the description doesn't significantly add meaning beyond the schema. Baseline 3 is justified.
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 function: 'Update thesis metadata: title, lifecycle status (active/paused/archived), webhookUrl.' It uses a specific verb ('update') and resource ('thesis metadata'), and lists the exact fields. It also distinguishes itself from a related sibling by pointing to configure_heartbeat for runtime heartbeat pause/resume, which differentiates it from a potentially overlapping action.
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 gives explicit guidance for one alternative: 'Use configure_heartbeat.paused for runtime heartbeat pause/resume.' This tells the agent when NOT to use this tool for a specific sub-action. However, it doesn't provide broader when-to-use guidance or comparisons to other siblings like create_thesis or update_strategy, though those are less ambiguous. The explicit exclusion earns a 4.
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.
