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submit_finding

OWNER ONLY — submit a structured research finding into News Guru's SharedBrain. kind: idea | anomaly | counterthesis | event. symbols and sources are comma-separated. Findings are context for the analyst agents; they never trigger trades directly. Requires an OWNER-tier API key (Bearer / X-API-Key / ?api_key=).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
kindYes
titleYes
missionNo
sourcesNo
symbolsNo
confidenceNo
event_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden and does well: it discloses the OWNER-only permission requirement, authentication methods, a notable non-effect (never triggers trades), and format hints for symbols/sources. It doesn't describe other side effects, but the key behaviors are covered.

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?

Four sentences, each carrying distinct information: purpose, kind values, format rules, and behavioral/authentication context. No filler, though it could have been slightly more organized with explicit parameter bullet points. Still concise and readable.

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?

For an 8-parameter tool with required fields, the description gives authentication, permission, and data-usage context, but leaves several parameters (e.g., mission, confidence, event_date) undefined, relying on schema naming. Output schema exists, so return values are likely self-explanatory, but overall completeness is moderate.

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 0%, so the description must compensate. It provides enums for 'kind' and comma-separation rules for 'symbols' and 'sources', which helps, but it leaves title, body, mission, confidence, and event_date without any semantic hints beyond their names. Partial compensation only.

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 states a clear action ('submit') and a specific resource ('structured research finding into News Guru's SharedBrain'), and it enumerates the valid kinds. It is easily distinguished from sibling tools, which are all read-only 'get' operations.

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 conveys when to use the tool: when submitting a research finding to SharedBrain, and it warns that findings do not trigger trades. It does not explicitly state when not to use it or name an alternative, but given the tool's uniqueness among siblings, the context is sufficient.

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

B3.4/5.0
Disambiguation5/5

Every tool targets a unique resource or data feed, from agent status and macro snapshots to Polymarket whale analytics and MLB props. There is no overlap or ambiguity between tools, even those within the same domain (e.g., the multiple Polymarket tools are clearly distinguished by their focus on landscape, stats, new wallets, leaders, and flagged whales).

Naming Consistency5/5

The naming follows a consistent get_<resource> pattern for all 35 data retrieval tools, with only verify_memecoin deviating but still using a clear verb-noun structure. The pattern is uniform and predictable, making it easy for an agent to infer the purpose of any tool.

Tool Count2/5

With 36 tools, this significantly exceeds the typical well-scoped range of 3-15. While the server covers a broad range of market intelligence domains, the sheer number of tools makes navigation and selection challenging for an agent, placing it in the 'too many' category.

Completeness4/5

The API provides comprehensive coverage across signals, sentiment, on-chain data, institutional activity, sports, and macro, with both broad aggregate tools and per-symbol/asset specifics. Minor gaps exist, such as a lack of direct news headlines or a fear-greed index, but these are not critical dead ends given the stated purpose of delivering derived intelligence.

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