Skip to main content
Glama

Tessera Analytics - Hyperliquid Market Intelligence

by dev.tesseralytics
OverviewDiscussionsAdmin

list_fields

Every field the query tools accept, each with its meaning, unit, whether it can be missing, and which bars (1d, 1h) it exists on. Open — no key needed. Call this before query_cross_section, screen_universe or query_series. Percentile, z-score and the top_pct/bottom_pct conditions rank within the markets your plan can see, so they need a wide slice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesYes
fieldsYesEvery field the query tools accept.
generated_atYesWhen this vocabulary was produced.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedOutput schema / $defs / FieldDoc / properties / grains
      Added value: +{
+  "description": "Plane grains on which this field is available, in canonical order.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedOutput schema / $defs / FieldDoc / properties / kind / description
      Previous value: -"`stored` (a column in the daily source) or `factor` (computed at query\ntime over a trailing window, or from the end-day row)."New value: +"`stored` (a column in the plane's own source) or `factor` (computed at\nquery time over a trailing window, or from the selected end row)."
    • changedOutput schema / $defs / FieldDoc / properties / nullable / description
      Previous value: -"Whether the value can be absent for a market on a day."New value: +"Whether the value can be absent for a market on a selected interval."
    • changedOutput schema / $defs / FieldDoc / required
      Previous value: -[
-  "name",
-  "meaning",
-  "unit",
-  "nullable",
-  "kind"
-]New value: +[
+  "name",
+  "meaning",
+  "unit",
+  "nullable",
+  "kind",
+  "grains"
+]
  2. Added

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the load; it discloses that access is open (no auth) and explains that percentile/z-score/top_pct/bottom_pct ranking is scoped to the markets a plan can see, which is non-obvious behavioral context. It does not state side-effect/read-only status explicitly, but a field catalog is implicitly read-only and the output schema covers the return shape.

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?

Three sentences, front-loaded with the payload description before prerequisites and semantics. The final sentence on plan-scoped ranking is informative but slightly tangential to a field-listing call, keeping it just short of a 5.

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?

With no inputs and an output schema present, the description need not explain return values; it instead covers the essentials an agent needs — what it returns, that it is keyless, when to call it, and the plan-scoped ranking caveat.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so per the rubric the baseline is 4; there is nothing for the description to disambiguate. The mention of 'bars (1d, 1h)' is descriptive of returned data, not of inputs.

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 precise resource ('every field the query tools accept') and enumerates the metadata returned per field (meaning, unit, nullable, available bars). An agent immediately understands this is a schema/catalog lookup, distinct from siblings like describe_dataset or list_datasets.

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 to 'Call this before query_cross_section, screen_universe or query_series', naming the exact downstream tools it feeds. Also notes it is open with no key needed, removing a common prerequisite question.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Tessera Analytics - Hyperliquid Market Intelligence toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources