apex_run_pandas_market_calendarsRun the allowlisted permissionless bounded pandas_market_calendars 5.4.0 calendar wrapper over supplied calendar/date parameters. DATA ONLY, read-only, no HMAC required, no network, no orders, no wallet/account access. Output declares data_as_of 5.4.0.
| Name | Required | Description | Default |
|---|---|---|---|
| calendar | Yes | ||
| end_date | Yes | ||
| start_date | Yes |
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?
Beyond the readOnlyHint annotation, the description discloses significant behavioral specifics: 'no HMAC required, no network, no orders, no wallet/account access' and that the output declares data_as_of 5.4.0. This goes well beyond the annotation and gives the agent confidence about side-effect-free, isolated execution. No contradiction with annotations; it reinforces them.
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 three sentences and every sentence earns its place: purpose, safety guarantees, and output version. It is front-loaded with the primary action, and there is zero fluff or repetition of schema fields.
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?
This is a simple tool with only 3 parameters and clear safety annotations. The description covers purpose, safety behavior, and a hint about output version. While there is no output schema and the exact return structure is not described, the tool is a well-known standard library wrapper, so the level of detail is sufficient for an agent to use it correctly. The only missing piece is a note about output shape or examples, but it's not critical for this simple use case.
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 compensate for explaining the parameters. It only vaguely refers to 'calendar/date parameters', which adds no meaning beyond the parameter names and schema constraints. The enum for calendar and the date patterns are in the schema but the description does not clarify semantics like what values are valid or what each parameter controls.
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 it 'Run the allowlisted permissionless bounded pandas_market_calendars 5.4.0 calendar wrapper over supplied calendar/date parameters' with a specific verb (Run), resource (pandas_market_calendars), and parameters. It is distinct from sibling tools that focus on other tasks like agent reviews, data profiling, or trading strategies, so there is no ambiguity about what this tool does.
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 excellent context for when to use this tool: it is 'DATA ONLY, read-only, no HMAC required, no network, no orders, no wallet/account access' and is 'permissionless and bounded'. This clearly signals safe usage contexts. However, it does not explicitly name alternatives or state when NOT to use it, though the unique domain (market calendars) makes alternatives unlikely.
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.
Most tools have clearly distinct purposes, and descriptions provide sufficient boundaries. Some run_* analytics tools (e.g., deflated_sharpe vs empyrical_metrics) could be conceptually confused, but their specific inputs and outputs minimize ambiguity.
All tools share the apex_ prefix, and the verb_noun pattern is consistent (get, query, run, submit). The 'agent_' subgroup within run tools introduces a minor irregularity, but it remains readily comprehensible.
With 24 tools, the server is on the heavy side, falling into the 16-25 range. Many run_* tools are similar in nature (pure calculations), but each appears to serve a specific purpose, so the count is borderline rather than excessive.
The server name implies a card store, yet the tool surface only supports reading and querying cards, with no create, update, or delete operations. This is a significant gap that prevents full lifecycle management, though the analytics side is fairly comprehensive.