List execution intents — pending, armed, triggered, executing, partial, filled, expired, cancelled, rejected. Shows the full execution pipeline status.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | Yes | SimpleFunctions API key. Get one at https://simplefunctions.dev/dashboard/keys | |
| status | No | Filter: pending, armed, triggered, executing, partial, filled, expired, cancelled, rejected | |
| activeOnly | No | Only show active intents (default true) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / status / descriptionPrevious value: -"Filter: pending, armed, triggered, executing, filled, expired, cancelled"New value: +"Filter: pending, armed, triggered, executing, partial, filled, expired, cancelled, rejected"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It states the tool lists intents and shows the full pipeline, which implies a read-only operation. However, it does not disclose potential side effects, permissions needed, or output format details, though for a list tool this is a moderate gap.
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 concise sentences with the purpose front-loaded. It provides essential information without redundancy, making it highly scannable for an agent.
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 low complexity, a list operation with optional filters, the description suffices by naming all statuses and indicating the full pipeline scope. It does not explicitly state return values, but no output schema exists; describing 'full execution pipeline status' implies the output. It could mention the activeOnly default, but that is already in the schema.
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 description coverage is 100%, so parameters are already well-documented. The description adds contextual meaning by listing the status filter values and introducing the concept of a pipeline, but does not provide additional details beyond the schema. 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 uses a specific verb ('List') with a clear resource ('execution intents') and enumerates all statuses, making the tool's purpose unambiguous. It distinguishes itself from sibling tools like create_intent or cancel_intent by focusing on listing the full pipeline.
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: use when you need to see execution intents. However, it provides no explicit guidance on when to use this tool over alternatives like get_orders or get_fills, or any exclusions like 'use cancel_intent to modify'. The context is clear but lacks comparative guidance.
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.