ping
Connectivity test.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Connectivity test.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 full burden for behavioral disclosure. 'Connectivity test' is minimal and does not disclose expected behavior (e.g., timeout, success criteria, side effects, or whether it's a read-only operation). It is essentially a tautology of the tool's name, providing little beyond the name itself.
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 words, extremely concise and front-loaded. It contains no unnecessary information and is appropriately sized for a tool with no parameters and a straightforward purpose.
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 has no parameters, no annotations, and no output schema, the description should compensate by explaining what connectivity test results look like or what the tool actually checks. It also does not disambiguate from the closely related sibling 'health_check'. The description is adequate for a trivial tool but leaves ambiguity about the exact scope and return value.
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 tool has zero parameters, so the baseline is 4. The description cannot add parameter meaning because there are none, and the schema already confirms no parameters exist. No further clarification is needed.
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 'Connectivity test' clearly states the tool's purpose with a concise verb-noun pair. It distinguishes from sibling tools which are all analytics/risk-related, making it obvious this is a low-level connectivity check. However, it could be slightly more specific about what connectivity means (e.g., network reachability, API availability).
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 guidance is provided on when to use this tool versus alternatives. The presence of sibling 'health_check' suggests potential overlap, but the description does not clarify whether to choose ping over health_check for service health assessments. It only states what the tool does, not when to use it.
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.
Tools like deadline_risk, early_warning, and evidence_decay have overlapping concerns about deadlines and warnings, though descriptions provide some distinction. Similarly, predict_article, predict_entity, and predict_score all cover predictions but differ in scope. Some ambiguity remains.
All names use snake_case, but the naming pattern mixes verb phrases (predict_article, trend_analysis) with noun phrases (deadline_risk, health_check), lacking a consistent verb_noun or noun_verb structure. This inconsistency can confuse an agent.
12 tools is well within the optimal 3-15 range for a specialized predictive analytics server. Each tool appears to serve a distinct function without unnecessary bloat or deficiency.
The tool set covers core predictive needs: deadlines, warnings, decay, scores, scenarios, trends, and remediation velocity. Missing are raw data access or configuration tools, but for a read-only prediction server, the surface is reasonably complete.