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Critique an architecture

critique_architecture
Read-onlyIdempotent

Validate your architecture design against rule-based checks to get scored findings before committing. Deterministic and free, with no model call or data storage.

Instructions

Check a design against SkeletIQ's architecture rules and get scored findings back. Deterministic and free — no model call, no credits, nothing stored. Useful on a design you drafted yourself before committing to it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoThe design's domain — e-commerce, fintech, healthcare, saas, social, iot, gaming, infrastructure, streaming, logistics, ai-ml, search, data-analytics, content-platform, internal-tool. Worth sending: the domain is what selects the compliance frameworks to check against, and without it none apply, so no compliance finding is possible and the score comes back higher than the SkeletIQ app would show for the same design — by up to 15 points.
exposureNoWhere the design runs. Worth sending: four checks — CDN, WAF, rate limiting and multi-region — ask whether traffic arriving from the public internet is handled safely, and they only apply to a system that takes any. Left unset, the design is assessed as internet-facing, which is why an air-gapped design comes back told to add a CDN. exposure_assessed says which exposure was actually used.
architecture_jsonNoA design to check. Free and deterministic — no model call. The shape SkeletIQ uses: title, description, components[{id,name,type,technology?}], connections[{source,target,protocol?}].
secondary_domainsNoFurther domains the design spans, when it spans more than one — a multi-tenant shop that takes payments is e-commerce plus fintech and saas. These select frameworks on top of the primary domain's, so leaving them off is why a design already checked against SOC2 and SOX in the app comes back here checked against neither, and scored higher for it. frameworks_checked says which were actually used.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
findingsYes
data_scoreYes
score_basisYesThis score is findings only. It is not held to a traceability ceiling, because this tool is given a design and no requirement set to trace it against. The app can show a lower number for the same stored design for exactly that reason.
finding_countYes
security_scoreYes
compliance_noteYes
resilience_scoreYes
exposure_assessedYesThe exposure this critique was actually run under. An absent or unreadable exposure is assessed as public_internet, so a value the server could not read shows up here rather than arriving silently as four extra security findings.
performance_scoreYes
architecture_scoreYes
frameworks_checkedYes
compliance_assessedYesFalse means no compliance framework was checked, so no compliance finding was possible.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

The description adds meaningful behavior beyond the annotations: 'Deterministic and free — no model call, no credits, nothing stored.' This clarifies side effects, cost, persistence, and repeatability, which is especially valuable for a read-only, idempotent tool.

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?

Three short sentences with no filler. The core action comes first, followed by key behavioral traits and a use-case tip. Every sentence earns its place.

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

Completeness4/5

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

The description, rich schema, annotations, and output schema together give the agent enough to use the tool correctly. A minor gap is that no top-level parameter is marked required, so the description could more explicitly signal that architecture_json is essential for a meaningful check.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The tool description itself doesn't add parameter-level meaning, but the detailed property descriptions already explain domain, exposure, architecture_json, and secondary_domains thoroughly.

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

Purpose5/5

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

The description states a specific verb and resource: 'Check a design against SkeletIQ's architecture rules and get scored findings back.' This clearly differentiates it from siblings like generate_architecture or check_drift, which create or compare rather than score a design against rules.

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

Usage Guidelines4/5

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

The description gives clear usage context: 'Useful on a design you drafted yourself before committing to it.' It doesn't explicitly mention when not to use it or name alternative tools, so it falls just short of full exclusion guidance.

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

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