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AI multi-analyst research briefing (HEADLINE)

research
Read-only

The differentiated endpoint: full briefing, bull case, bear case, valuation, investment plan, fair-value range. Bills against your ai_research quota (50/day at $99/mo, $0.10 overage). Currently returns cached results only; fresh-trigger via API arriving next release. (GET https://app.deepvalues.ai/api/v1/research/{ticker} — 3 credits per call; needs a connected account or a dv_sk_ key)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYes
languageNoEnglish

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior5/5

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

Annotations only cover readOnly/openWorld, but the description adds substantial behavior: quota (50/day at $99/mo, $0.10 overage), 3 credits per call, cached-only status, and auth requirements (connected account or dv_sk_ key). This is exactly the kind of cost/auth/state disclosure an agent needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the value proposition well, but then crams pricing, quota, caching, URL, credit cost, and auth into one trailing parenthetical. The information is useful but the structure is dense and slightly cluttered rather than cleanly ordered.

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?

With no output schema, the description covers what is returned, cost, caching state, and auth—enough for an agent to call it safely. The gaps are the unexplained 'language' parameter and the missing routing guidance versus sibling research tools.

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

Parameters2/5

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

Schema description coverage is 0% across 2 params, so the description must carry the load and it largely does not. It mentions {ticker} only via the URL template and never explains the 'language' enum, so an agent gets no added semantic meaning for either parameter.

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?

States a specific verb/resource ('full briefing, bull case, bear case, valuation, investment plan, fair-value range') and frames itself as 'The differentiated endpoint.' However it does not distinguish itself from close siblings like mirror_brief, verdict, or theses, so the agent still has to guess which briefing tool to pick.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance or routing versus siblings (mirror_brief, verdict, intrinsic_value). The note that it 'currently returns cached results only' hints at a limitation but does not tell the agent when this tool is the right choice.

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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