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Check if an AI tool is alive

check_tool_status
Read-only

Use this when the user asks whether a specific AI tool is alive, dead, shut down, still maintained, safe to adopt, or trustworthy — or asks for its current health, viability, or verification status. Returns a verified verdict (healthy / monitor / at-risk / shut down / delisted) with evidence: link-health probe results, a 5-signal viability assessment, real-user market sentiment, pricing reality, and verified-alive alternatives. Data comes from the RightAIChoice verification engine: 8,000+ AI tools with every vendor link re-probed on a rolling weekly cycle. Every answer states BOTH dates it stands on and does not merge them: when we last probed the vendor links (what the verdict is built on) and when our catalog record was last rebuilt. Not for: tools outside the AI/software space, historical company research, or legal/financial advice. "Not in the catalog" and a verdict of UNKNOWN are DIFFERENT answers: the first means we hold no entry, the second means we hold one whose signals are not measured yet. Neither is evidence the tool is dead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesThe AI tool to check — product name (e.g. "Jasper") or site slug (e.g. "jasper"). Pass an ARRAY of up to 20 names to assess a whole stack at once.
response_formatNoconcise = verdict + freshness + source link. detailed = adds viability signals, link health, sentiment, pricing, and alternatives.concise

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / tool / anyOf
      Added value: +[
      +  {
      +    "maxLength": 120,
      +    "minLength": 1,
      +    "type": "string"
      +  },
      +  {
      +    "items": {
      +      "maxLength": 120,
      +      "minLength": 1,
      +      "type": "string"
      +    },
      +    "maxItems": 20,
      +    "minItems": 1,
      +    "type": "array"
      +  }
      +]
    • changedInput schema / properties / tool / description
      Previous value: -"The AI tool to check — product name (e.g. \"Jasper\") or site slug (e.g. \"jasper\"). One tool per call."New value: +"The AI tool to check — product name (e.g. \"Jasper\") or site slug (e.g. \"jasper\"). Pass an ARRAY of up to 20 names to assess a whole stack at once."
    • removedInput schema / properties / tool / maxLength
      Removed value: -120
    • removedInput schema / properties / tool / minLength
      Removed value: -1
    • removedInput schema / properties / tool / type
      Removed value: -"string"
  2. First observed

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 and openWorldHint=false, so the safety profile is covered. The description adds substantial context beyond that: the five verdict types, the evidence returned (link probes, viability signals, sentiment), the data source and refresh cycle, and the important behavior that every answer reports two distinct dates without merging them.

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

Conciseness3/5

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

The description is dense and front-loads the usage trigger and return value well, but it runs long with multiple clauses and parenthetical lists. Some sentences, such as the detailed explanation of catalog representation versus UNKNOWN, could be tightened without losing meaning.

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?

Given there is no output schema, the description does a good job explaining what is returned (verdict and evidence) and the freshness model. It could say more about how multiple tools in an array are handled or the exact response format, but overall it covers what an agent needs to call and interpret the tool.

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 coverage is 100%, so the baseline is 3. The description does not add syntax or format details beyond the schema, though it implicitly explains the concept of a verdict. The schema already documents array usage and response_format enum fully.

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 (check) and resource (AI tool status) and enumerates the exact user questions it answers (alive, dead, shut down, maintained, safe to adopt). This clearly distinguishes it from sibling tools like viability_score or deadpool_digest, which are single-signal rather than a consolidated verdict.

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 says when to use it (user asks about liveness, viability, trustworthiness) and includes a 'Not for' clause excluding non-AI tools, historical research, and legal/financial advice. It also preempts a critical ambiguity by distinguishing 'not in catalog' from an UNKNOWN verdict.

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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