Skip to main content
Glama

get_software_stats

Read-only

Software landscape

The free host-software landscape (issue #490): k-anonymised vendor share (k=5, the sub-k tail folded into other), version distribution within each named vendor, ASN hosting share, and a two-denominator coverage block (host-weighted ~90% and participant-weighted ~50%, each named, no bare coverage scalar). Computed live from the temporal software table and edge-cached. Names no operator. Keyless-cacheable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.2/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite readOnlyHint already declaring the safety profile, the description adds substantial behavioral context: k=5 anonymisation, tail folding into 'other', two-denominator coverage, no bare coverage scalar, live computation, edge caching, keyless cacheability, and no operator naming. These details materially affect how the returned data must be interpreted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but purposeful: it opens with the subject, then explains the exact metrics, denominator treatment, computation method, and caching characteristics. Every clause supplies a meaning or caveat; only the issue number is mildly unnecessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the full burden of explaining the return meaning. It covers the metric set, k-anonymisation, denominator nuance, temporal characteristics, and caching. An agent has enough context to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and schema coverage is 100%, so the description bears no burden for explaining inputs. The 0-parameter baseline applies: there is nothing meaningful to add beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource: a current 'Software landscape' of free host software, listing vendor share, version distribution, ASN hosting share, and coverage metrics. It does not use an explicit verb like 'returns' or 'lists', and it does not explicitly distinguish itself from get_software_stats_history, so it loses the top point.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The text implies this is the current snapshotted landscape ('Computed live ... edge-cached'), which suggests use for current software stats rather than historical ones. However, it never names get_software_stats_history or gives explicit when-to-use/when-not-to-use guidance, so the usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation4/5

Most tools are cleanly separated by resource type: participants, access points, hosts, providers, incidents, anomalies, and SLA each have their own get/list vocabulary. The main ambiguous pairs are get_provider_sla vs get_provider_sla_by_key, list_providers vs list_public_providers, and get_summary vs get_network_summary.

Naming Consistency4/5

The overall get_/list_ verb_noun pattern is consistent and readable, and plural/singular resource names are mostly clear. There are a few exceptions: get_provider_sla and get_country_providers return collections despite using get_, and list_provider_certs is more of an aggregate posture endpoint than a simple list.

Tool Count2/5

43 tools is well beyond the typical well-scoped MCP surface and will make the tool set harder for an agent to navigate defensibly. The tools are systematically grouped, but this looks like a broad REST API surface rather than a compact, purpose-fit MCP server.

Completeness5/5

For a read-only monitoring and directory domain, the coverage is unusually complete: list/detail endpoints, histories, SLA tables, churn breakdowns, anomalies, incidents, adoption aggregates, software landscape, and quality checks are all represented. The drill-down routes such as churn totals to churn participants also avoid dead ends.

Resources