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Web audit summary

get_audit_summary
Read-only

Web audit health summary for a project: site health score, its change since the last crawl, and the top-3 prioritized fixes.

project_id is a ranking id from list_projects. The fix-next verdict explains why each item matters and which area it touches, alongside quick wins, pages at risk, and what was fixed since the last crawl. Free — calling it never consumes lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixedYes
fix_nextYes
project_idYes
quick_winsYes
since_lastYes
health_deltaYes
health_scoreYes
pages_at_riskYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds value beyond that by specifying the output contents and by stating that calling it never consumes lookups, which is a meaningful behavioral/cost guarantee.

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?

The description is front-loaded with the core result and keeps the remaining details in two compact sentences. Every sentence adds relevant information, though the second sentence is somewhat dense with output components.

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?

Given the single required parameter and the presence of an output schema, the description is complete for invoking the tool. It explains the parameter source, the output highlights, and the free/no-lookup behavior, leaving no critical gap for correct use.

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?

With 0% schema description coverage, the description compensates by explaining that project_id is a ranking id from list_projects. This gives the agent a concrete source for the value, though it stops short of a full format example or additional constraints.

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 exactly what the tool returns: a web audit health summary with site health score, change since last crawl, and top-3 prioritized fixes. This scope clearly differentiates it from siblings like get_audit_issues by focusing on the health summary rather than raw issue listing.

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 description tells the caller that project_id should come from list_projects and that the call is free, which is useful context. However, it does not explicitly say when to prefer this tool over related siblings such as get_audit_issues or get_project_overview, leaving the choice to inference.

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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TDQS

A3.7/5.0
Disambiguation3/5

Most tools are distinct get_* analytics, but several overlap in purpose: get_ai_visibility vs get_share_of_voice are easy to confuse, and get_project_overview/get_content_action_plan/get_audit_summary all offer prioritized fixes. Descriptions help, but an agent could easily misselect for a generic 'what should I fix?' query.

Naming Consistency5/5

All names follow a consistent snake_case verb_noun pattern (add_, get_, generate_, list_, analyze_, research_), and the get_* prefix dominates read operations. Even win_prompt is a verb_noun and fits the style.

Tool Count2/5

27 tools is past the 25+ threshold and creates a heavy selection surface for an agent. While the SEO/AI-visibility domain is broad, many tools return overlapping 'health/fix/visibility' data and the set would benefit from consolidation.

Completeness3/5

Core workflows (projects, keywords, content briefs, audits, backlinks, AI visibility) are covered, but lifecycle gaps exist: keywords and AI prompts can be added but not removed, there is no list-AI-prompts tool, and no project creation/update is exposed. These are workable but notable missing operations.

Resources