Get the live operational status of every major AI service tracked by TensorFeed (Claude, ChatGPT, Gemini, Perplexity, Cohere, Mistral, HuggingFace, Replicate, Midjourney, etc). Polled every 2 min. Returns operational | degraded | down per service plus the most recent incident.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses polling frequency (every 2 min) and output format (operational|degraded|down per service plus most recent incident). No annotations provided, so description carries burden well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with front-loaded purpose and list of services; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, output, and update frequency. Lacks error handling or auth details but sufficient for a simple read-only status check.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist (0 params), so baseline 4 applies. Description does not need to add parameter detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and resource 'live operational status of every major AI service tracked by TensorFeed' with explicit examples. Distinct from sibling tools like check_agent_reputation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Does not explicitly state when to use vs alternatives, but the purpose is self-evident and no close sibling tools exist, so missing exclusion guidance is less critical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several security/vulnerability tools (check_ai_supply_chain_risk, get_cve_record, get_osv_advisory_by_id, get_osv_advisory_for_package) have overlapping purposes, making it potentially confusing to choose the right one. Other tools are more distinct, but the ambiguity in this cluster lowers the score.
All names are snake_case and mostly follow a verb_noun pattern, but the verbs are inconsistent (check, get, list, lookup, query, register, route, search, submit, whats_new). Some tools use 'get' while others use 'check' for similar retrieval actions, and 'whats_new' does not fit the verb_noun pattern.
With 27 tools, the count exceeds the 25 threshold for 'too many', even though the broad scope spans many domains. The sheer number makes the server feel heavy and harder to navigate.
The server covers a wide range of data domains, but notable gaps exist: no management of watch subscriptions (only register), no CVE search, and no model search. Write operations are minimal, leaving some workflows incomplete.
