The Investment Panel's read on one ticker: its Chophouse doneness grade (RAW..CHARRED, how much value is already cooked in) plus every seat's vote across 11 emulated investor lenses, with the registry verdict for context. The panel advises, the reader decides. Says so if the ticker is not plated yet.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | US ticker, e.g. NVDA |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the return values (grade, votes, verdict) and hints at error behavior for unknown tickers, but lacks detail on side effects, permissions, or rate limits. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that combines key information but uses metaphorical language and extraneous phrasing ('The panel advises, the reader decides'). Could be more concise while retaining essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains the return values and covers an error scenario. It provides a reasonable mental model of what the tool does, though some behavioral aspects are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one required parameter (ticker). The description adds no new meaning beyond the schema's description ('US ticker, e.g. NVDA'). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a doneness grade (RAW..CHARRED) plus votes from 11 investor lenses and a registry verdict for a single ticker. It distinguishes from sibling tools like get_stock_quote and list_reports, though the metaphorical 'Chophouse' language may be slightly unclear for an AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description mentions an error case ('if the ticker is not plated yet') but does not compare to siblings like get_scorecard or provide selection criteria.
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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Each tool has a clearly distinct purpose: getting panel grades, auditing past signals, fetching live quotes, listing reports, and publishing reports. No overlaps or ambiguity.
All tool names follow a consistent verb_noun pattern using lowercase with underscores (get_panel_grade, get_scorecard, get_stock_quote, list_reports, publish_report). No mixed conventions.
With 5 tools, the set is well-scoped for the domain of investment signals and reports. Each tool serves a necessary function without redundancy or excessive bloat.
Covers key operations: viewing individual panel grades, auditing past signals, getting live quotes, and managing reports. A minor gap is the lack of a tool to view full report content, but list_reports may provide summaries and the set is otherwise complete.
