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Liminal

by ai.physea
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research

Web research question answered with fetched, cited findings. More args: get_capabilities(tool=...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesDescribe the user's goal in one short sentence. Omit personal data and secrets.
questionYes
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "question",
-  "context"
-]New value: +[
+  "question",
+  "context",
+  "llm_model"
+]
  2. Changed5 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Describe the user's goal in one short sentence. Omit personal data and secrets.",
+  "type": "string"
+}
    • removedInput schema / properties / max_depth
      Removed value: -{
-  "default": 3,
-  "title": "Max Depth",
-  "type": "integer"
-}
    • removedInput schema / properties / question / title
      Removed value: -"Question"
    • changedInput schema / required
      Previous value: -[
-  "question"
-]New value: +[
+  "question",
+  "context"
+]
    • removedInput schema / title
      Removed value: -"researchArguments"
  3. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It adds some value by signaling the output is fetched and cited (external network use, citation-bearing results), but it discloses nothing about latency, cost, rate limits, or what happens with the data submitted.

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?

Two short clauses, purpose front-loaded first, no filler. The trailing "More args" pointer is slightly cryptic, but the overall size is appropriate for the tool's simplicity.

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?

There is no output schema and no annotations, and the description omits the cost/latency profile and any description of the 'question' parameter, so it is only minimally complete for a 3-required-param tool that performs external fetches.

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 67%, and the description adds no meaning about any parameter beyond pointing to get_capabilities for more detail. The unnamed 'question' param is undocumented in both schema and description, but the schema covers the other two adequately for a baseline 3.

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?

It names a concrete verb+resource: answering a web research question with fetched, cited findings. That is clear enough for an agent to understand the operation, but it never distinguishes itself from siblings like solve or read, so a 4 rather than a 5.

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?

"More args: get_capabilities(tool=...)" does route the agent to a sibling for additional argument details, which is useful. However, it gives no when-to-use / when-not-to-use guidance, no prerequisites, and no comparison to the solve or read tools that might overlap.

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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