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List projects

list_projects
Read-only

List your Ranklogs projects, flattened into rows: project_id, domain, tracking type, engine/locale, keyword count, and top-line movement.

Each row's project_id is a ranking id you pass to other tools. tracking_type is web, local, or YouTube. Demo/sample projects are flagged is_demo — do not treat them as the customer site. Call this tool first to get valid project_id values before calling anything else. Free — calling it never consumes lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
verdictYes
projectsYes
truncatedYes

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that the call is free and never consumes lookups, and warns that demo/sample projects are flagged is_demo and must not be mistaken for customer sites. This is behaviorally useful context not present in the annotations.

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 tightly written sentences: the first states the output and columns, the second clarifies project_id and tracking_type, and the third adds the demo caveat plus cost/first-call guidance. Every sentence earns its place with no filler.

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 tool has an output schema, the description does not need to restate return values. It covers output structure, project_id reuse, demo flags, cost behavior, and the recommended call order, so an agent has enough context to invoke it correctly.

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 has one optional limit parameter with zero description coverage, and the tool description never mentions limit. Since the description is expected to compensate for low schema coverage but does not, the parameter semantics are under-specified, though the parameter is optional and nominally self-explanatory.

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?

States a specific verb ('List') and resource ('Ranklogs projects') and enumerates the flattened output columns. It also positions the returned project_id as the value to pass to other tools, which distinguishes this foundational listing tool from sibling get_* tools.

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?

Explicitly instructs the agent to call this tool first to obtain valid project_id values before calling anything else. The additional note that it is free and never consumes lookups further clarifies when it is safe to use.

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.

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