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Liminal

by ai.physea
OverviewDiscussionsAdmin

focus

Pass a URL or long text plus task; returns the answer-bearing passages verbatim. Use instead of opening anything over 8,000 chars. More args: get_capabilities(tool=...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
textYes
contextYesDescribe the user's goal in one short sentence. Omit personal data and secrets.
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: -[
-  "text",
-  "task",
-  "context"
-]New value: +[
+  "text",
+  "task",
+  "context",
+  "llm_model"
+]
  2. Changed7 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 / detail
      Removed value: -{
-  "default": "lean",
-  "title": "Detail",
-  "type": "string"
-}
    • removedInput schema / properties / retention
      Removed value: -{
-  "default": "task_local",
-  "title": "Retention",
-  "type": "string"
-}
    • removedInput schema / properties / task / title
      Removed value: -"Task"
    • removedInput schema / properties / text / title
      Removed value: -"Text"
    • changedInput schema / required
      Previous value: -[
-  "text",
-  "task"
-]New value: +[
+  "text",
+  "task",
+  "context"
+]
    • removedInput schema / title
      Removed value: -"focusArguments"
  3. Changed1 schema field changed
    • addedInput schema / properties / detail
      Added value: +{
+  "default": "lean",
+  "title": "Detail",
+  "type": "string"
+}
  4. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the output shape (verbatim answer-bearing passages rather than a summary) and a size threshold that hints at cost. It says nothing about side effects, whether the input is stored or transmitted, or permission/rate characteristics, which matters for a tool that ingests user text.

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 short sentences, front-loaded with the core behavior, then the routing rule, then the pointer for extra detail. Zero filler; every clause carries information.

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?

For a 4-required-param tool with no output schema, the description covers what goes in, what comes back, and when to prefer it, plus a pointer to get_capabilities for deeper detail. It remains thin on side-effect/privacy behavior and on the two undocumented parameters, so it is strong but not exhaustive.

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 50%: context and llm_model are documented in the schema, while task and text are bare. The description partly compensates by explaining that 'text' may be a URL or long text and that 'task' is the question being asked, but it leaves both underspecified (no size/format guidance) and the 'More args' pointer is cryptic.

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 concrete verb+resource action (pass text plus task, get answer-bearing passages verbatim) rather than a restatement of the name. It implicitly distinguishes itself from the sibling 'read' by describing itself as the replacement for opening long content, so an agent can route correctly without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit, quantified use condition ('anything over 8,000 chars') and names the alternative it substitutes for (opening/reading), which is a real routing rule. It does not spell out the inverse case in words or say what to do for shorter inputs, so it stops just short of the 5 bar.

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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