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Compound Interesting — market intelligence

Tickers ranked by consensus strength

rank_consensus
Read-only

The names where independent actors agree most strongly, ranked. Use this to find candidates rather than to check one you already have in mind.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many rows to return.
directionNoRestrict to one consensus direction.
min_signalsNoMinimum number of dimensions that voted.
min_agreementNoMinimum agreement score, 0-1.

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds context about 'independent actors agree most strongly' (the ranking logic), but doesn't mention operational details like default ordering, pagination, or what happens when filters are omitted. This is adequate but not rich.

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?

Two concise, front-loaded sentences: the first states what the tool does, the second gives usage guidance. No redundant words or repetition of schema details.

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 read-only ranking tool with 4 optional, well-described parameters and no output schema, the description gives enough purpose and usage context. It could mention how filters interact with ranking, but the presence of schema descriptions and the readOnly annotation keeps it complete enough for selection.

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 description coverage is 100% – every parameter has a description (limit, direction, min_signals, min_agreement). The tool description adds no additional parameter meaning beyond the schema, so the baseline of 3 is appropriate.

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?

The description clearly states it returns 'names where independent actors agree most strongly, ranked' – a specific verb+resource (ranked list of consensus names). It distinguishes from siblings by contrasting with 'to check one you already have in mind', making its screening purpose explicit.

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?

The description explicitly says 'Use this to find candidates rather than to check one you already have in mind' – giving clear when-to-use direction and an implicit when-not-to-use. It doesn't name alternative tools, but the contrast is strong enough to guide selection.

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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TDQS

A4.2/5.0
Disambiguation3/5

get_composite and get_consensus both return per-ticker consensus with dimension breakdowns, creating ambiguity; agents might call the wrong one. Other tools are clearly distinct, but this overlap requires extra care.

Naming Consistency5/5

All tools follow a verb_noun pattern: get_ for single entities, list_ for collections, and rank/search/screen as action verbs. The pattern is consistent and predictable across the entire set.

Tool Count5/5

15 tools is well-scoped for a market intelligence server, covering single-ticker queries, lists, discovery, and market-level signals without unnecessary bloat.

Completeness4/5

The surface covers core workflows: ticker resolution, consensus, evidence, trades, positioning, screening, and market signals. Minor gaps exist (e.g., historical consensus or direct ticker comparison), but they are not critical.

Resources