ElkassabgiData

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

Annotations provide readOnlyHint=true; description adds value by noting the key is masked and never echoed, and explains how to configure the key.

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?

Single sentence with no wasted words, front-loaded with the key purpose.

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 simple auth status check, the description is sufficient despite lacking output schema details.

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?

No parameters exist (schema coverage 100%), baseline 4 applies. Description adds meaning by explaining the tool's purpose and output.

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 checks whether an API key is configured and provides instructions for adding one, distinguishing it from sibling tools that handle data retrieval.

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 usage for verifying connection setup, but does not explicitly state when to use or not use this tool, nor mention alternatives.

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?

The description adds value beyond the readOnlyHint annotation by explicitly stating that dates are never fabricated and that silent upstream outages show as stale. This provides honest behavioral insight into data quality and failure handling.

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 sentences long, front-loads the core concept ('Live per-source update status'), and wastes no words. Every phrase 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?

Given that there is no output schema, the description adequately summarizes what the tool returns (last successful update, data frontier, stale/failure flags). It provides behavioral context and usage guidance, though a more detailed enumeration of return fields would make it 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?

The input schema already describes the parameter as 'One source id; omit for the full board' (100% coverage). The tool description repeats this in slightly different words ('per-source... omit for the full board'), adding no new semantic meaning beyond a casual tone.

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 it provides 'live per-source update status' with specific outputs: 'last successful update, data frontier, and honest stale/failure flags'. This verb+resource combination is distinct from all sibling tools, which focus on auth, economics, or family status.

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 specifies usage with 'per-source' and 'omit for the full board', giving clear context. It does not explicitly state when not to use or list alternatives, but the sibling tools are sufficiently different that no confusion arises.

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 the description adds valuable context about API key requirement and output format (long format rows with citation/license). This goes beyond the annotation, though rate limits or error handling are omitted.

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 sentences, front-loads the core purpose, and includes key usage guidance without any unnecessary words.

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 and 25% schema coverage, the description provides essential purpose, usage, and output format. It lacks details on default max_rows behavior and error handling, but is fairly complete for a data download 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 description coverage is only 25% (only series_id described). The description adds meaning for date_from/date_to (window long series) but does not explain max_rows or date_to beyond the schema. It partially compensates for low coverage.

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 downloads an economic time series in long format with date, value, citation, and license. It distinguishes from siblings like search_econ_series and get_econ_series_metadata by focusing on data retrieval.

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 explicitly mentions the required API key and guides windowing with date_from/date_to. However, it does not provide explicit when-not-to-use or alternative tool references.

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, so the description adds value by noting 'Free, no key needed' and listing metadata fields. However, it doesn't disclose rate limits, pagination, or edge cases like non-existent series. The description is adequate given the simple read-only nature.

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 sentence that is front-loaded with purpose and lists key fields. Every word is essential, and it avoids redundancy.

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 simple tool with one parameter and no output schema, the description lists metadata fields but does not specify the return format (e.g., object vs array, JSON structure). It is fairly complete for its simplicity but could still clarify the series_id format and provide usage examples.

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?

With 0% schema description coverage, the description must provide parameter semantics. The only parameter 'series_id' is not explained at all (e.g., format, examples, how to obtain it). The description adds no meaning beyond the schema, which just lists it as a string.

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 it provides 'Full metadata for one econ series' and lists specific fields like title, frequency, geography, etc. It distinguishes from siblings like 'get_econ_series' (which likely returns data values) and 'search_econ_series' (searching).

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 mentions it's 'Free, no key needed,' which is helpful for usage context. It implies this tool is for metadata rather than data values, but does not explicitly state when to use vs alternatives like 'get_econ_series'.

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 indicate readOnlyHint=true, so the tool is safe. The description adds 'Live' (real-time) and 'Free' (no cost), and specifies that it returns headline stats and data currency. While helpful, it does not disclose rate limits or response details, but the annotations reduce the burden.

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 concise sentence that effectively communicates the tool's purpose, scope, and key traits (live, free). No wasted words.

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 parameters and no output schema, the description is adequate for a simple read-only tool. However, it does not describe the exact fields or format of the returned data, which could help an agent understand what to expect. Still, it is functional.

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 are zero parameters and schema coverage is 100%, so the baseline is 4 per guidelines. The description does not need to add parameter meaning since none exist.

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 provides 'live status of the whole ElkassabgiData family' with 'headline stats and data currency', specifying the verb (get implied), resource (family status), and scope (whole family). It partially distinguishes from siblings like get_data_freshness by emphasizing the family-level view, but could be more explicit.

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 on when to use this tool vs alternatives such as get_data_freshness or get_auth_status. The description mentions it is free, but does not provide usage context 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?

The readOnlyHint annotation already indicates this is a safe read operation. The description adds that it returns download instructions rather than data, and requires authentication. This provides useful context beyond annotations, but is not extensive.

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 three sentences long, each providing essential information: purpose and scope, delivery mechanism, and authentication requirement. No superfluous words or repetition.

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 tool has 4 parameters and no output schema, the description should cover what is returned (a download link) and explain all parameter options. It omits details on 'quality' and 'version' datasets, and the exact return format is implicit ('instructions'). This leaves gaps for an agent to fully understand tool behavior.

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 50% (descriptions for format and ticker only). The description adds context for dataset ('bars or the 25 pre-computed academic variables') and format ('parquet or csv'), but does not explain the 'quality' dataset option or the 'version' parameter (clean vs. raw). Thus it partially compensates for the schema's gaps.

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 provides authenticated download instructions for specific datasets (1-minute OHLCV bars or pre-computed academic variables), including scope and format options. This distinguishes it from sibling tools like get_hf_variables_dictionary, which likely returns metadata.

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 context on when to use the tool (to obtain download links for full-history data) and mentions that files are fetched by user code, implying this is not for inline data. However, it does not explicitly exclude alternatives or state when not to use it.

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. The description adds context about the content (verbatim dictionary definitions) but no additional behavioral details beyond that.

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?

Single sentence, no wasted words. Efficiently conveys the tool's purpose and content.

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 no-parameter tool, the description is sufficient: it specifies what is returned (definitions/formulas) and that it's free. Could be slightly more complete by noting it's static and read-only.

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?

No parameters in schema (0 params) so baseline is 4. Description doesn't need to add parameter meaning.

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 provides exact definitions/formulas of 25 pre-computed academic variables, listing specific families. It is well-differentiated from sibling tools like get_hf_download_link or search_econ_series.

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 it's 'Free' but lacks context for 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?

The annotations already declare readOnlyHint=true, so the bar is lower. However, the description adds no further behavioral context beyond listing and including licenses. It does not disclose potential issues like pagination, rate limits, or caching behavior. With minimal added value, a score of 2 is appropriate.

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 sentence that gets to the point quickly. The phrase 'Free.' seems tacked on but does not detract significantly. It is concise and front-loaded with the verb 'List'. Minor structural improvement possible.

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 simple list tool with one optional parameter and no output schema, the description is fairly complete. It provides the count, types, and licenses. It lacks details on output format, but that is acceptable given no output schema. Adequate for the tool's simplicity.

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% for the one parameter 'contains', which includes a description and an example. The tool description does not add any new meaning beyond what the schema already provides. Baseline 3 is correct.

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 verb 'List' and the resource 'Econ Data Library's sources', specifies the scope (309 sources of types like statistical offices, central banks, IGOs, research datasets) and mentions licenses. It distinguishes this tool from siblings like 'search_econ_series' and 'get_econ_series', which focus on series, not sources.

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 does not provide any guidance on when to use this tool versus alternatives. It only mentions 'Free', which is not a usage guideline. There is no mention of prerequisites, when-not to use, or links to sibling tools.

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. Description adds that the tool is free and requires no key, helpful for authentication context. No mention of rate limits or pagination, but sufficient given read-only nature.

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 waste. Front-loaded with core purpose, then authentication and output usage. Excellent conciseness.

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 3 parameters and no output schema, description covers purpose, output usage, and authentication. Lacks pagination or error behavior details, but largely complete given tool simplicity and sibling context.

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 67% with examples for query and source. Tool description adds no parameter-specific information beyond schema, so 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 it searches the Econ Data Library catalog, listing billions of series from 300+ sources. It distinguishes from siblings like get_econ_series by specifying it returns series ids.

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?

Explicitly says 'Free, no key needed' indicating zero authentication. Suggests workflow by noting results are usable with get_econ_series. Lacks explicit when-not scenarios but provides sufficient context.

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