TradingAgentStack

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

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds no behavioral context beyond that. It doesn't confirm read-only behavior, explain side effects, mention authentication needs, or clarify the nature of the external interaction.

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, short sentence with a clear front-loaded topic ('Who places the order...') and a list of modes. It is not verbose, though its phrasing as a question rather than an action statement slightly undermines clarity.

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?

For a tool with no parameters and only read-only/open-world annotations, the description still fails to state the operation being performed. An agent cannot determine whether invoking it retrieves the current gating mode, sets a policy, or does something else entirely.

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?

The tool has zero parameters, so there are no parameter semantics to describe. The baseline for a parameterless tool is 4, and the description neither adds nor detracts from parameter understanding.

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 names the domain (broker MCP servers and order placement) and lists possible gating modes, but it never states what the tool actually does. It does not specify whether it reads, sets, or otherwise manipulates the gating policy, leaving the core verb absent.

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?

There is no guidance on when to use this tool, what prerequisites exist, or how it relates to alternatives such as compare_tools or get_tool. The description only presents possible order-placement modes without indicating when an agent should invoke the tool.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only one behavioral detail beyond that — results are 'with sources' — but says nothing about return format, ordering, or behavior when a slug is invalid.

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?

A single front-loaded sentence that packs the action and three scope qualifiers with no filler. Nothing could be removed without losing meaning.

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?

For a two-parameter comparison tool with no output schema, the description needs to carry more weight on identifier semantics and result shape. It is adequate for an agent that already knows the slug convention but leaves real gaps for one that does not.

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 description coverage is 0% and neither slug_a nor slug_b is described anywhere. 'Two tools' weakly implies each slug identifies a tool, but the description gives no format, source, or constraint (e.g., where a slug comes from, whether both must exist), so the parameters remain ambiguous.

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?

Clear specific verb 'Compare' plus resource 'two tools', with useful scope detail ('side by side, field by field, with sources'). It distinguishes itself from get_tool/list_category by the pairwise comparison framing, though it never names a sibling to reinforce the contrast.

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?

The description states what the tool does but never says when to prefer it over get_tool (single lookup) or search_tools (discovery). No prerequisites, no when-not conditions, and no routing hint are given; the agent must infer usage from the name alone.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds what the content actually contains (pricing, live vs paper, order approval, rate limits, safety score inputs, source URLs), which is more than the annotations provide. It doesn't cover missing-slug behavior or freshness, so not a 5.

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?

One compact sentence with a colon-delimited payload list, front-loaded with the verb and resource. No filler.

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?

For a single-parameter read-only lookup with no output schema, the description tells the agent what facts come back and that URLs are included. Minor gaps remain: behavior for unknown slugs and whether the response is a fixed shape.

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 a single slug parameter whose description already says 'from search_tools or name'. The description adds no syntax or format detail beyond that, so the baseline 3 applies.

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?

States a specific verb (get) and resource (one tool) and enumerates the exact payload: pricing, live vs paper, order approval, rate limits, safety score inputs, source URLs. This clearly distinguishes it from search_tools, which is referenced in the schema as the source of the slug.

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?

The schema description says the slug comes from search_tools, which implies the lookup pattern, but the tool description itself gives no explicit when-to-use versus compare_tools, list_category, or broker_order_gating. Usage is inferable from the payload list but not stated.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds one behavioral trait beyond that -- unknown category values return the category list rather than failing -- but says nothing about ordering, pagination, or how errors on the primary path behave.

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?

Two sentences, no filler, with the core purpose front-loaded and the fallback behavior second. Nothing could be removed without losing information.

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?

For a one-parameter, read-only lookup with no output schema, the description covers purpose, the parameter's nature, and a non-obvious fallback path. The only real gap is the missing contrast with sibling tools, which is in a different dimension.

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 the slug format and an example ('broker_mcp') already documented in the schema. The description only adds the indirect semantic that unrecognized values are tolerated, which is a minor increment over the structured field.

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 states a specific verb and resource ('List every tool in a category'), which is clear enough to separate it from get_tool and search_tools despite never naming them. The purpose is unambiguous, but it stops short of explicitly contrasting itself with the siblings that also surface tools.

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?

It offers one concrete calling pattern -- pass an unknown category to enumerate categories -- which is a useful discovery trick. However, it never says when to prefer this tool over search_tools or get_tool, so the primary routing decision is left implicit.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the useful scoping fact that results come from a curated tool directory and that filters are optional, but says nothing about result limits, ranking, or pagination.

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?

Two tight sentences: the core action first, then the optional filters. No filler, no redundancy, nothing to trim.

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?

For a search tool with no output schema, the description omits what a result actually contains (tool names, slugs, links, matched fields) and how results are bounded or ranked. Annotations cover safety, but return-shape expectations are left unspecified.

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 description coverage is 100% with clear per-parameter descriptions, so the schema carries the parameter burden. The description merely restates the filter set ('category slug, can_trade_live, has_paper') without adding format, matching, or combination semantics.

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?

States a specific verb+resource ('Search the TradingAgentStack directory of AI trading tools') plus the dimensions searched (name, market, feature). It is naturally distinguishable from get_tool and list_category, but it never explicitly names or contrasts those siblings.

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?

The description surfaces the optional filters, implying this is the keyword-driven discovery path, but it gives no explicit when-to-use vs. compare_tools/get_tool/list_category and no when-not guidance. Usage is left to inference.

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