SecurityScan catalog: tiers, prices, quotas and the evidence behind the product — the fact sheet an agent needs to evaluate or recommend a purchase to its user. Fully offline, no API key required.
Returns: JSON with the tier table (price / target slots / scan types), the pricing model, benchmark evidence, and how to buy.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | 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?
No annotations are provided, so the description carries the full burden and delivers: 'Fully offline, no API key required' discloses network and authentication behavior, and the Returns clause discloses the payload shape. For a zero-parameter read-only catalog this is strong disclosure. It does not state data freshness or explicitly assert zero side effects, but nothing in the text implies mutation.
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 tightly written and front-loaded: purpose and audience in the first sentence, behavioral constraints in the second, return contents in the third. The Returns clause is slightly redundant given the existing output schema, but it adds the 'how to buy' pointer and keeps the description scannable. No wasted words.
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 tool of minimal complexity (0 params, no annotations, output schema present), the description is complete: it states what the tool is, who it serves, its connectivity/auth posture, and the shape of what it returns, and it hints at the next step ('how to buy') toward the checkout sibling. Nothing an agent needs in order to call it correctly is missing.
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 takes zero parameters and schema description coverage is trivially 100%, so the rubric's 0-param baseline of 4 applies. The description reinforces that no input is needed by presenting the tool as a self-contained static fact sheet ('Fully offline, no API key required'). A 5 would be unwarranted since there are no parameters for the description to actually document.
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 defines a specific resource and scope: 'SecurityScan catalog: tiers, prices, quotas and the evidence behind the product'. It frames the audience and use ('the fact sheet an agent needs to evaluate or recommend a purchase'), and implicitly distinguishes from sibling securityscan_checkout by situating this tool at the evaluation stage. The 'Returns: JSON with...' clause makes the retrieval semantics unambiguous even without an imperative verb.
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 phrase 'the fact sheet an agent needs to evaluate or recommend a purchase to its user' gives an explicit when-to-use context: purchase evaluation and recommendation. The mention of 'how to buy' in the return payload hints that actual purchasing belongs elsewhere, namely the sibling securityscan_checkout. However, it never names an alternative explicitly or states when not to use this tool, so it stops short of a 5.
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 target distinct scan types (MCP config, dependencies, skills, network, secrets), but full_stack_audit deliberately overlaps with five of them, creating ambiguity about whether to call the umbrella tool or a focused scanner. The descriptions mitigate this by clarifying scope, but the redundant surface makes selection less crisp.
Names are mostly descriptive and action-oriented, but they mix conventions: scan_secrets and scan_skill use a verb_noun pattern, audit_mcp_server_config and check_dependencies use different verbs, network_scan and full_stack_audit are non-verb phrases, and securityscan_checkout/securityscan_pricing use a brand prefix. This is readable but not a consistent, predictable pattern.
With 8 tools, the server is well-scoped for its security-scanning purpose. Each focused tool covers a meaningful threat surface, and full_stack_audit adds value as a correlation layer rather than pure bloat.
The toolset covers the core security lifecycle for an agent environment: configuration auditing, dependency health, skill vetting, network scanning, and secret/PII redaction, plus a full-stack correlation option. Minor gaps exist around remediation actions and persistent scan history, but these are not clearly required by the server's stated purpose.