TSRE Swedish Equity Intelligence

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

With no annotations, the description carries the full behavioral burden. It discloses the payload categories and a meaningful caveat that this is decision support rather than a trade signal, but says nothing about data freshness/cadence, auth requirements, or rate limits for a 'latest' daily report.

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 names the resource first and appends the caveat last. Every clause carries information; nothing is redundant padding.

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 present, the enumerated return categories are a bonus rather than a necessity, and the lack of parameters removes most ambiguity. The remaining gap is operational context (refresh cadence, availability) that a daily-report tool would benefit from.

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 there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. 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?

States a specific verb (Retrieve) and resource (TSRE Daily Investment Desk for Swedish equities) and enumerates the payload's contents. It does not differentiate itself from the sibling report_agent_data_demand, but the purpose is unambiguous on its own.

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 clause 'Research decision support; not an autonomous buy/sell signal' hints at the intended use context, but the description never states when to call this versus the sibling tool or what prerequisites/preconditions apply. Usage is implied rather than specified.

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?

No annotations are provided, so the description carries the full burden. It adds valuable behavioral context: voluntary participation, no impact on other tools, and explicit warnings against submitting secrets, personal data, keys, or confidential info. It also asks about external tool support and authorized payment. It doesn't state if the data is stored, anonymized, or how it's used, which would be helpful.

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 of moderate length, front-loaded with the purpose and then details. Every sentence adds useful information, though it could be slightly tightened.

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 annotations, 8 undocumented parameters, and an output schema, the description is incomplete. It lacks parameter guidance and doesn't mention what happens after submission (e.g., response format, privacy policy). The output schema might cover return values, but input semantics 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 0% and there are 8 parameters with no descriptions. The description does not explain what each parameter should contain (e.g., market, data_need, current_task) or provide examples. It only vaguely mentions indicating external tool support and authorized payments, which maps to a few parameters but lacks specificity.

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 a specific action (report an unmet need for external data or computation) and frames it as optional market research. It is distinguishable from get_sweden_market_intelligence, a data retrieval tool. However, the phrase 'machine-to-machine market research' is slightly ambiguous and could be clarified.

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 provides clear context: it's for agents working on real research, investment, or data-analysis tasks, and explicitly says participation is voluntary and not required for other tools. It names domains of interest but doesn't explicitly state when not to use it beyond that.

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