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Site Doctor — WordPress diagnosis

get_site

Site state. The default view:'summary' is TOKEN-CHEAP (~1-2k tokens): verdict, critical/warning counts, availability + WAF-blocked flag, finding TITLES only, fix-proposal counts, recent events, and a _hint on where to drill down. Use it to orient. Pass view:'full' ONLY when you truly need the whole record (full findings with evidence, worklog, forms, decisions, proposals with rollback text, accesses) — it is large (tens of thousands of tokens). Prefer drilling down with get_findings / get_events / get_worklog / a targeted probe op over pulling the full record. Fix proposals show which fixes are active on the site — check them before proposing a new fix or diagnosing behavior a prior fix may explain.

Input Schema

NameRequiredDescriptionDefault
site_idYesSite id from list_sites

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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 does so well: it quantifies cost (~1-2k tokens vs tens of thousands), enumerates exactly what each view contains, and explains why the cheap view suffices for orientation. It also discloses a non-obvious side benefit (fix proposals reveal active fixes that may explain current behavior).

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

Conciseness4/5

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

Front-loaded with the default/cheap path, then the escape hatch, then alternatives, then the fix-proposal caveat — a sensible ordering. Dense but every clause adds routing value; only the final sentence could be tightened.

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

Completeness3/5

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

For a no-output-schema read tool the description covers return content and cost well, but it is incomplete in a critical way: the view mode it spends most of its text on is absent from the input schema, leaving an inconsistency the agent must resolve on its own. No guidance on error behavior or what happens if site_id is invalid.

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

Parameters2/5

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

The schema documents only site_id at 100% coverage, but the description centers on a `view` parameter ('summary'/'full') with enum-like semantics that does not appear anywhere in the input schema and has zero enum entries in the structured data. An agent reading the schema cannot pass this parameter, so the description's most prominent parameter guidance is unusable and potentially misleading.

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 opening 'Site state' is terse, but the following sentences make the function concrete: it returns a site record in a token-cheap summary view (verdict, finding titles, counts, events) or a full record. It distinguishes itself from siblings by naming get_findings / get_events / get_worklog as drill-down alternatives.

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

Usage Guidelines5/5

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

Explicit when-to-use ('use it to orient'), when-NOT to use the expensive mode ('Pass view:full ONLY when you truly need the whole record'), and named alternatives for drilling down. It also gives a situational trigger for checking fix proposals before proposing a new fix.

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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