fetch_fact
Paid. Fetch one AAPL filing fact (SEC 10-K/10-Q). $0.01 USDC on Base to 0x5fB2FAeaAbd58Da0eA1E1F64a8C2134c4941eFe5. URL https://southpow.media/v1/fact?id=AAPL.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Fact id | AAPL |
Paid. Fetch one AAPL filing fact (SEC 10-K/10-Q). $0.01 USDC on Base to 0x5fB2FAeaAbd58Da0eA1E1F64a8C2134c4941eFe5. URL https://southpow.media/v1/fact?id=AAPL.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Fact id | AAPL |
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 carries the full burden. It discloses the cost ($0.01 USDC) and provides payment details, which is important. However, it does not clarify whether the tool initiates payment or if the user must pay separately, nor does it mention error behavior, rate limits, or response format. It adds some behavioral context but leaves key aspects ambiguous.
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 sentence with all essential information, but it front-loads 'Paid.' which is important context. The payment and URL details are concise but could be separated for readability. Overall, it is efficient and not verbose.
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 paid tool with no output schema and no annotations, the description is insufficient. It lacks clarity on the payment mechanism (who pays, when), the response format, error handling, and whether non-AAPL ids are valid. It also does not mention siblings for routing. An agent would have uncertainty about how to correctly invoke and interpret results.
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%, so the schema already documents the 'id' parameter as 'Fact id'. The description adds no meaningful enrichment; instead, it suggests the parameter is fixed to AAPL, which contradicts the schema's default and potential extensibility. This could mislead an agent about the parameter's scope.
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 states a clear verb ('Fetch') and resource ('one AAPL filing fact (SEC 10-K/10-Q)'), which is specific. However, it implies only AAPL, while the schema allows any id via the default parameter, creating a slight mismatch. It does not name sibling tools to differentiate, but the purpose is distinct enough.
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?
No explicit guidance on when to use this tool versus get_schema or search_facts. The payment requirement is mentioned but not framed as a selection condition. The description implies it is for fetching a single known fact, but this is not stated as a rule or alternative.
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 has a distinct purpose: fetch_fact retrieves a specific fact, get_schema provides the schema, and search_facts lists available facts. No overlapping functionality.
All tools follow the consistent verb_noun pattern (fetch_fact, get_schema, search_facts), which is clear and predictable.
Three tools is a well-scoped set for a simple fact-fetching API, covering the essential operations without unnecessary bloat.
The tool set covers the full lifecycle for this domain: searching for facts, retrieving a specific fact, and understanding the data structure via the schema. No obvious missing operations.