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

Annotations already establish readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds genuinely new behavioral context: the data is sourced from a 'daily scan', which signals freshness/staleness characteristics, plus that the response includes current screen-pass status. It stops short of stating refresh timing or caching.

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 dense sentence with the subject ('one stock') up front and the payload enumerated after the colon. No filler, no restatement of the tool name.

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?

An output schema exists, so explaining return values is optional; the description instead usefully previews them. For a read-only two-parameter getter this covers what an agent needs, with only the routing question (when to prefer a screen or market view) left open.

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% and both parameters carry examples and a pointer to list_markets, so the schema does the heavy lifting. The description adds no parameter-level detail (no mention of the market dimension or its US default), which is acceptable at this coverage level but earns no bonus.

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 a single specific resource ('one stock') and enumerates the exact payload an agent can expect (RS ratings, stage, scores, growth, group rank, setup/pattern fields, passing preset screens). That makes it clearly distinguishable in spirit from aggregate siblings like market_overview and group_rankings, though it never names or contrasts them directly. Strong but not sibling-differentiating.

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 when-to-use guidance, no condition selecting this over run_screen or market_overview, and no note that list_markets should be consulted for valid market codes. The single-stock framing implies the use case, but nothing is stated explicitly.

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 analytic context (relative strength, 1W/1M/3M/6M rank change windows, weekly movers, constituent detail), but says nothing about data freshness, rate limits, or how the ranking universe is derived.

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 with no filler; the analytical scope is front-loaded and the group-passing instruction follows. Slightly dense/run-on in the first sentence but well structured overall.

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?

An output schema exists, so return values need not be explained, and the description covers ranking content and the group-detail mode adequately. However, the 'limit' parameter is completely undocumented and no relationship to sibling tools is given, leaving gaps for a 3-param listing tool.

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 67% and the description adds real meaning only for 'group' (its rank history and strongest stocks), which extends the schema's terse 'detail and constituents'. The 'limit' parameter is undocumented in both schema and description, and 'market' is already covered by the schema, so the description does not fully compensate for the gap.

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 a specific analysis (IBD-style industry group rankings by relative strength) plus the timeframes and extras returned, so the resource and verb are unambiguous. It does not differentiate itself from siblings like market_overview or run_screen, which is the only thing keeping it from a 5.

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 sentence 'Pass a group name for its rank history and strongest stocks' implicitly tells the agent the two modes of use (list rankings vs. drill into one group), which is useful. There is no explicit when-not-to-use guidance and no sibling alternative is named, so usage remains implied rather than 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 only the vague scope 'current publish'; it says nothing about pagination, filtering, data freshness guarantees, or what 'published features' actually means.

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?

It is a single short sentence with no filler, which is appropriately sized for a zero-parameter list tool. It reads as a fragment rather than a front-loaded statement of purpose, which slightly weakens the structure.

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?

An output schema exists, so return values need not be explained, and annotations cover the safety profile. Still, for a tool whose sibling set contains a directly overlapping market_overview, the description omits the routing information an agent needs to choose correctly.

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 takes zero parameters, so per the rubric the baseline is 4. Nothing in the description is needed to disambiguate inputs, and no misleading parameter claims are made.

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 resource (markets) and scopes it to the 'current publish', and lists the fields surfaced (data date, status, published features). However it is a noun phrase with no verb and gives no differentiation from siblings like market_overview or list_screens, leaving the agent to infer that this is a listing tool.

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 when-to-use guidance, no exclusions, and no mention of alternatives such as market_overview, which overlaps heavily with this tool. The agent gets no signal about which sibling to pick.

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, covering the safety profile. The description adds that the output includes exact rules per screen and that ids are the handoff key to run_screen, but says nothing about auth, pagination, or catalog size, which is a modest addition over annotations.

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 short sentences with zero filler. The purpose and the id/run_screen handoff are both front-loaded and immediately actionable.

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?

An output schema exists, so the description needn't explain return values, and the catalog-plus-id workflow is fully conveyed. The only minor gap is that market filtering is left entirely to the schema.

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% and the single market parameter is fully documented in the schema (including the pointer to list_markets), so the schema does the heavy lifting. The description mentions no parameters at all, so 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?

The description states the resource concretely — preset screens such as Minervini, CANSLIM, VCP — and adds that each carries its exact rules, so the agent knows it is retrieving a catalog of screening strategies rather than screen results. It doesn't explicitly contrast itself with siblings beyond naming run_screen as the consumer, so it falls short of a 5.

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?

"Pass a screen's id to run_screen" gives the agent a clear two-step workflow: call list_screens to discover ids, then feed them to run_screen. That is real guidance on when this tool is appropriate versus run_screen, though no exclusions or edge cases are 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 safety and external-data scope are covered. The description adds the content scope of the payload but says nothing about data freshness/delay, caching, or cost — relevant for market data, though not required given the annotations and the output schema.

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 with no filler; every clause maps to a returned data category. The parenthetical enumerations are dense but each earns its place by telling the agent what the payload contains.

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?

With an output schema defining the return shape, read-only/open-world annotations covering the safety profile, and a single well-documented optional parameter, the definition is largely sufficient. The missing piece is usage routing — when to prefer this over group_rankings or run_screen — and any note on data recency.

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?

There is one optional parameter (market) with 100% schema description coverage, including a default of 'US' and a pointer to list_markets. The description adds nothing about the parameter, so the baseline 3 applies since the schema carries the 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?

Names a concrete deliverable (a market-health snapshot) and enumerates the specific content it aggregates: exposure score/stance, breadth metrics, index moves, and leading industry groups. An agent can tell it apart from get_stock or run_screen, though no sibling is named explicitly to sharpen the boundary.

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 phrase 'in one call' implies this is the consolidated first-stop for market context, which is a weak usage signal. There is no explicit when-to-use statement, no prerequisites, and no named alternative (e.g., group_rankings for drill-down).

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 and openWorldHint, so safety is covered. The description adds real behavioral context beyond that: the scan covers every listed stock daily, a preset reproduces exactly what the website shows, and filters AND together with the preset. It omits pagination/limit behavior and result shape, though an output schema exists.

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?

Three short sentences, front-loaded with the core action and scope, and each sentence carries information. The parenthetical on 'every listed stock' and the website-fidelity sentence are justified, though slightly more text than strictly needed.

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?

With six optional parameters, an output schema, and read-only annotations, the description supplies the missing conceptual glue (preset vs filter, AND semantics, scan scope). The main gap is routing guidance among siblings and any note on the 1-100 limit default of 25, which the agent must read from the schema.

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 83%, so the baseline is 3, but the description genuinely adds semantics the schema does not: filters are AND-combined and are also ANDed with the preset. It does not explain limit, sort_by inheritance from the preset, or descending beyond what the schema says.

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 ('Run a preset screen and/or custom filters') and scopes it to a market's full daily scan over every listed stock, which separates it from list_screens (preset ids) and get_stock (single symbol). It stops short of naming any sibling explicitly, so it is clear but not sibling-differentiated by name.

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?

'and/or' plus 'Filters are combined with AND, including with the preset' implies both are optional and combinable, and 'the project's website shows for it' hints at what a preset returns. However, there is no explicit when-to-use guidance, no statement of prerequisites (e.g. that screen ids come from list_screens), and no exclusions versus market_overview or group_rankings.

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