fetchPobiera pełną kartę reputacji numeru po id zwróconym przez search (9 cyfr). Zwraca te same dane co check_phone_number wraz z linkiem do strony numeru.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Id z wyników search: polski numer, 9 cyfr |
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?
Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds a meaningful behavioral detail: it returns the same data as check_phone_number plus a link to the number's page. However, it doesn't describe error handling or edge cases, which is acceptable given the low complexity and annotation coverage.
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 action, and contains no fluff. Every word serves a purpose, and it remains concise while conveying key details about input and output.
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 simplicity (1 parameter, annotations present, no output schema), the description is sufficient. It explains the input source and the output relationship to check_phone_number, providing enough context for an agent to use the tool correctly. Slight deduction for not detailing the exact return structure, but this is mitigated by the 'same data as check_phone_number' reference.
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 has 100% coverage for the single parameter 'id', and the description essentially repeats what the schema already states (Polish number, 9 digits). No additional semantic value is added beyond the schema, so the baseline of 3 applies.
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: fetching a full number reputation card by ID returned from search. It also specifies the ID format (9 digits) and distinguishes this from check_phone_number by noting it returns the same data plus a link to the number's page.
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 indicates when to use this tool (after obtaining an ID from search) and contrasts it with check_phone_number, implying this is a more complete variant. While it doesn't explicitly mention alternatives or exclusions, the context provides sufficient 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.
Some tools overlap in functionality: check_phone_number and check_scam_domain both accept phone numbers, and search and find_official_number both return official numbers. The descriptions differentiate them, but an agent might be unsure which tool is best for a given query.
Tool names follow mixed conventions: check_phone_number and check_scam_domain use verb_noun, fetch and search are bare verbs, recent_scam_domains is adjective_noun, and spam_weather is noun_noun. There is no consistent naming pattern across the set.
With 7 tools, the set is well-scoped for a phone and scam reputation service. Each tool has a distinct role, and the count feels neither sparse nor bloated.
The tool surface covers the domain comprehensively: phone number reputation, scanning suspicious messages, finding official numbers, listing recent scam domains, and providing aggregate statistics. There are no obvious dead ends or missing core operations.