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

There are no annotations, so the description carries the full burden. It reveals that the output is 'computed' and 'compact,' but does not disclose whether the call has side effects, whether it triggers expensive computation, how symbols affect the result, or any permissions or data dependencies. This is a meaningful transparency gap.

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 no redundant filler. The main purpose and the key usage constraint are front-loaded, and every clause adds signal. This is appropriately concise and well structured.

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?

Although an output schema exists and can describe return values, the description still leaves essential gaps: parameter semantics are unexplained, computation behavior is vague, and there is no guidance about prerequisites or side effects. For a tool with no annotations and no schema-level parameter documentation, this is insufficient.

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 the description does not mention trade_date or symbols at all. It refers to SH, V, and JM in the output scope, but never explains how these relate to the parameters or what values are valid. The agent gets no help understanding the input contract beyond raw names.

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 action ('Return') and a specific resource ('compact computed packet for SH, V, and JM'), so an agent can tell roughly what the tool produces. It also marks itself as 'the only market payload that should enter the report context,' which helps differentiate it from sibling report and data tools, though it does not name those alternatives.

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 gives clear usage context: this is the only market payload that should enter the report context, implying it should be used for report construction rather than raw data collection or storage. It does not explicitly list when not to use it or name alternatives, but the 'only market payload' phrasing provides a strong selection rule.

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?

With no annotations provided, the description carries the behavioral disclosure burden. It clearly discloses that the tool validates and upserts data and that it 'returns counts only, not the submitted dataset,' which is highly useful. It does not detail validation rules or side effects, but the primary behavioral expectations 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.

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

Two sentences with no filler: the first states the operation and scope, the second clarifies the return behavior. It is front-loaded and every sentence earns its place.

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 the single `records` array parameter and a well-defined nested schema, the description is largely sufficient. It tells the agent what data is being submitted, the write behavior, and the response shape. Minor gaps such as explicit sibling routing and field-level format details are not severe enough to reduce completeness.

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 schema has 0% description coverage, so the description should compensate. It adds some meaning by listing acceptable metric categories like 'spot, inventory, operating-rate,' which clarifies the `metric` field, but it does not explain the required per-record fields (trade_date, symbol, metric, value) or value formats. The nested schema remains self-explanatory enough for a 3.

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 operation ('Validate and upsert') and the resource ('structured spot, inventory, operating-rate, or other daily metrics'). The title and tool name also reinforce that this is for manual daily metric submission, which distinguishes it from the report/research-focused sibling 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?

The phrase 'spot, inventory, operating-rate, or other daily metrics' implies the tool is for submitting daily metric data, and the title suggests manual entry. However, there is no explicit guidance on when to prefer this tool over siblings like report_save or research_search, nor any stated exclusions.

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?

With no annotations, the description must carry the behavioral burden; it does disclose that only run status is returned and that the operation is a configured execution. However, it does not explain potential side effects, authorization requirements, or what 'supported' means, leaving the tool's impact underspecified.

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 front-load the action and the key output limitation without wasted words. The structure is clean and easy to parse.

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?

The output schema presumably documents the run-status return, so that gap is covered, but the tool is under-specified for invocation: source values, date format, and the meaning of 'supported' are absent. Given a two-required-parameter tool with no annotations and zero schema description coverage, the description is not sufficient for correct use.

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 0% and the description does not explain the 'source' parameter's allowed values or how it selects between crawler and FuturesIntelTool, nor does it specify the 'trade_date' format. The mention of 'one supported symbol and date' is confusing because the schema contains no symbol parameter.

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 identifies a clear action ('Run') and a resource ('configured native crawler or FuturesIntelTool refresh') scoped to a symbol and date, which distinguishes it from the sibling reporting/search tools. The 'or' between two run targets and the unexplained 'supported' qualifier keep it from being fully precise.

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 guidance is given about when to invoke this tool versus any sibling, and no alternative tools are named. The scope ('one supported symbol and date') implies a constrained use case, but the description never states prerequisites or exclusions.

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?

With no annotations, the description carries the full behavioral disclosure burden. It clearly states the tool returns only compact metadata and summaries, and makes a strong guarantee that full report content is never returned. It does not describe ordering or pagination, but those are minor for a list tool with an 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?

Two sentences with zero filler. The key result type and limitation are front-loaded, and the workflow guidance is delivered in a compact second sentence.

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?

The description provides a clear workflow and output boundary, and the output schema covers return values. However, with 0% schema coverage and no annotations, the filtering behavior is left entirely to inference. A complete list-tool description should at least hint at how query, date range, and symbols narrow results.

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%, so the description needed to explain the five filter parameters. It does not mention limit, query, date_from, date_to, or symbols, nor how they interact. The parameter names are conventional, but the description adds no semantic value beyond them.

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 uses a specific verb ('Return') and resource ('past reports'), and specifies the exact result scope: 'compact report metadata and short summaries only.' The phrase 'full report content is never returned' clearly differentiates it from a full-content retrieval tool like report_read.

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 explicitly says to use this tool 'before reading any past report,' which establishes when it belongs in the workflow. It also warns that full report content is never returned, implying this is not the tool for full-content access, but it does not name a specific sibling as the alternative.

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?

With no annotations provided, the description must carry behavioral disclosure. It does reveal that reading is token-budgeted and supports offset-based continuation, which is useful. However, it does not state side effects, permissions, or that the actual schema parameter is named 'offset' rather than 'next_offset,' which undercuts transparency.

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 two short sentences with the core action front-loaded and no filler. The second sentence adds useful pagination guidance, though the imprecise 'next_offset' name is a minor blemish. It is appropriately sized for a simple read tool.

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?

The core read behavior and token/pagination handling are present, and the output schema covers return shape. However, with no annotations, the description leaves gaps around tool-selection context, offset semantics, and when reading is appropriate versus listing or searching. It is minimally viable but not fully complete.

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%, so the description must compensate. It loosely maps 'token budget' to max_tokens and 'next_offset' to offset, but uses a parameter name that does not exist in the schema. report_id is only implied by 'selected report,' so the compensation is partial and somewhat misleading.

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 opens with 'Read one selected report,' giving a clear verb and object, and it distinguishes the tool from siblings like report_list and report_save by focusing on consuming a single report's contents. The phrase 'selected report' implies an existing report_id, though the resource type is not spelled out. Overall, the purpose is clear and identifiable.

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 tool's role is implied: use it when you have selected a report and want to read its content. However, it provides no explicit guidance about when to prefer report_read over report_list, daily_report_context, or research_search. The only concrete usage instruction, 'Use next_offset to continue only when necessary,' is about pagination rather than tool selection.

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?

With no annotations, the description carries the behavioral burden. It discloses the upsert behavior: re-saving the same date, type, title, and source updates the existing report. However, it does not mention side effects, persistence guarantees beyond 'outside model context', or what happens on failure.

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, front-loaded with the core purpose, followed by the key behavioral detail. No filler or redundancy; every sentence adds value.

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?

The tool has nested payload parameters, no parameter descriptions, and no annotation context. The description clarifies persistence and update semantics but omits critical invocation details such as required field formats, defaults, valid report types, or how to structure the payload.

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 the description does not explain the payload structure or field semantics. It only references 'date, type, title, and source' in the context of re-saving, which provides minimal insight into required parameters like content, summary, symbols, or trade_date.

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 action: 'Persist a completed report outside model context.' This clearly identifies the operation and resource, and the title aligns. It does not explicitly distinguish from sibling tools like manual_data_submit, but the focus on 'completed report' and persistence is fairly unique.

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 implies when to use the tool: when a report is completed and needs to be persisted outside model context. It does not explicitly discuss alternatives, exclusions, or when not to use this tool, so usage guidance is only 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?

With no annotations, the description carries the burden, and it does usefully disclose the max result count and output shape ('at most three short excerpts with citations'). However, it does not disclose failure behavior, access requirements, or how the result limit relates to the limit parameter.

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 with no filler; the primary action is front-loaded and the return constraint is stated directly. It is concise and scannable for an agent.

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 an output schema, missing return details are less critical, but there is no explanation of the optional symbols filter or query semantics. Because annotations are absent and schema description coverage is 0%, an agent is left without enough context to reliably build a query.

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 0% and the description does not name or explain query or symbols; the only implicit hint is 'at most three' mapping to the limit default. Since the schema itself has no descriptions, the description should compensate but only partially does.

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 clear search action over named sources ('FuturesIntelTool or native news, announcements, and research notes') and explicitly says it returns excerpts with citations. The resource is somewhat ambiguous because 'FuturesIntelTool' is not defined, but it does differentiate from generic report 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?

No guidance about when to prefer this over sibling tools such as report_read or daily_report_context, and no exclusions or conditions. It only implies searching research content; an agent must infer when this is the right tool.

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